Mischa Andriessen - run.unl.pt

D zal een astronaut zijn die lelijk

zijn enkel verzwikt in de krater,

die hij als eerste te laat ontdekte.

Mischa Andriessen

I declare that this dissertation and the data presented are the result of my own work, as developed between 2010 and

2014 in the laboratory of Dr. Lars Jansen at the Instituto Gulbenkian de Ciência in Oeiras, Portugal. Where appropriate,

specific contributions by colleagues and collaborators are acknowledged in the Author Contributions section and by co-

authorship.

Declaro que esta dissertação é da minha autoria e que os dados aqui incluídos são o resultado de trabalho original por

mim desenvolvido entre 2010 e 2014 no laboratório do Dr. Lars Jansen no Instituto Gulbenkian de Ciência em Oeiras,

Portugal. Sempre que apropriado, contribuições específicas dos colegas e colaboradores são reconhecidos na seção

Author Contributions e por co-autoria.

Financial support was granted by Fundação para a Ciência e a Tecnologia, doctoral fellowhip SFRH/BD/74284/2010.

Apoio financeiro da FCT e do FSE no âmbito do Quadro Comunitário de apoio, BD nº SFRH/BD/74284/2010.

To be defended at the Instituto Gulbenkian de Ciência in Oeiras, Portugal on the 8th of June 2015, before a jury

composed of:

Prof. Bill Earnshaw (Wellcome Centre for Cell Biology, Edinburgh, UK);

Prof. Kerry Bloom (UNC, Chapel Hill, NC, USA);

Dr. Reto Gassmann (IBMC, Porto, PT);

Dr. Jorge Carneiro (IGC, Oeiras, PT);

Dr. Lars Jansen (IGC, Oeiras, PT);

and presided over by a yet to be determined representative of ITQB

Printed in February, 2015

Dani Bodor

i

Table of C0ntents

Summary — p.ii; Resumo em Português — p.iii; Acknowledgements — p.iv;

List of Publications — p.ix

1. General Introduction: Epigenetics, Centromeres, and

Quantitative Biology P.1

Epigenetics — p.3; Centromeres — p.19; Quantitative Biology — p.34;

References — p.46

2. Analysis of Protein Turnover by Quantitative SNAP-Based

Pulse-Chase Imaging P.71

Introduction — p.73; Pulse-Chase — p.77; Quench-Chase-Pulse — p.81;

Combining SNAP Experiments with Cell Synchronization and RNAi — p.85;

Live Imaging of Pulse Labeled Cells — p.91; Automated Quantification of SNAP-

Tagged Protein Turnover at Centromeres — p.95; Supporting Protocols —

p.102; Background Information — p.108; References — p.117; Appendix:

Maps of SNAP- and SNAPf-tags — p.120

3. Assembly in G1 phase and Long-Term Stability are Unique

Intrinsic Features of CENP-A Nucleosomes P.125

Introduction — p.127; Results — p.129; Discussion— p.144; Material and

Methods — p.147; References — p.151; Supplementary Figures — p.155;

Appendix: The Role of CENP-C in CENP-A Dynamics— p.158

4. The Quantitative Architecture of Centromeric Chromatin P.163

Introduction — p.165; Results — p.166; Discussion— p.184; Material and

Methods — p.190; References — p.199; Figure Supplements — p.207

5. General Discussion; Or, What I’ve Learned and What I Have to

Say about It P.215

Non-Centromeric CENP-A — p.217; The Ultrastability of CENP-A — p.221;

Mass Action vs. Ultrastability — p.228; The Critical Amount of CENP-A —

p.232; Concluding Remark — p.237; References — p.238

ii

Summary

A PhD is like a box of chocolates, …… and in this thesis I will present

what I got. My work has been focused on a cellular structure that is essential

for accurate genome inheritance: the centromere. Centromeres are

chromosomal domains that do not rely on the presence of any specific DNA

sequence. Rather, they are determined by the presence of a histone variant

called CENP-A. Stable transmission of CENP-A containing chromatin is

accomplished through 1) an unusually high level of protein stability, 2) self-

directed recruitment of nascent CENP-A near existing molecules, and 3)

strict cell cycle regulation of assembly. Together, these features lead to a

self-sustaining loop that allows for epigenetic maintenance of centromeres.

My own contributions to the understanding of epigenetic centromere

inheritance are of a quantitative nature. To put my work in context, I will

start with an extensive INTRODUCTION of epigenetics, centromeres, and

quantitative biology. Next, in CHAPTER 2, I will detail two of the main

methodologies that have allowed for the quantitative analysis of centromere

inheritance in subsequent chapters. These are, firstly, fluorescent SNAP-

based pulse-labeling, used to distinguish between old and new protein

pools; and secondly, a macro for ImageJ that I have developed, allowing for

the accurate and unbiased quantification of fluorescence signals at

centromeres. In CHAPTER 3, the cis requirements for assembly and extreme

stability of centromeric nucleosomes are analyzed. I demonstrate that both

G1 phase loading and long-term centromeric retention are unique features

of the (CENP-A/H4)2 subnucleosomal core, and are self-directed through

a CENP-A encoded targeting domain. CHAPTER 4 provides a quantitative

analysis of centromeric chromatin. The absolute number of CENP-A

molecules at centromeres has been determined in addition to its

quantitative regulatory mechanism and distribution. Finally, an overarching

DISCUSSION of my results is presented, providing an outlook on how my

findings can guide future centromere research.

iii

Resumo em Português

Um doutoramento é como uma caixa de chocolates, ..... e nesta tese vou

apresentar o que eu consegui. O meu trabalho focou-se numa estrutura

celular essencial para fidelidade do processo de herança do genoma: o

centrómero. Centrómeros são regiões cromossômicas que não dependem da

presença de nenhuma sequencia de ADN específica. Invés, são determinados

pela presença de uma histona chamada CENP-A. A transmissão estável de

cromatina contendo CENP-A é possível graças 1) a uma inusual alta estabi-

lidade da proteina, 2) o auto recrutamento da CENP-A nascente com base na

presença da proteína antiga, 3) e um alto nível de regulação da sua incor-

poração durante o ciclo celular. Em conjunto, estas princípios asseguram um

ciclo auto sustentável de manutenção epigenética dos centrómeros.

A minha contribuição para a compreensão da herança epigenética do

centrómero é de natureza quantitativa. Para contextualizar o meu trabalho,

começo com uma INTRODUÇÃO extensa da epigenética, dos centrómeros, e da

biologia quantitativa. No CAPÍTULO 2, detalho duas das metodologias que

foram usados nos capítulos seguintes para a análise da herança centromé-

rico. Estas são, primeiro, marcação fluroescente baseada em SNAP-tagging,

usada para distinguir as populações de proteinas antigas e novas; e segundo,

uma macro de ImageJ desenvolvida por mim, que permite a quantificação

dos sinais fluorescentes do centrómero de uma maneira precisa e imparcial.

No CAPÍTULO 3 são analizados os requerimentos em cis da incorporação e

estabilidade extrema dos nucleossomas CENP-A. Demonstro que, ambas

incorporação na fase G1 e retenção centromérica a longo prazo, são pro-

priedades únicas da estrutura sub nucleossomal (CENP-A/H4)2, e definidas

por um domínio intrínseco de CENP-A. O CAPÍTULO 4 fornece uma análise

quantitativa da cromatina centromérica. O número absoluto de moléculas de

CENP-A nos centrómeros foi determinado, assim como o aspecto quantita-

tivo do mecanismo da sua regulação e distribuição. Por último é apresentada

uma DISCUSSÃO abrangente dos meus resultados e do impacto que as minhas

descobertas trazem na orientação da futura investigação centromérica.

iv

Acknowledgements

Honestly, I don’t really know where to begin. So many people have been

helpful and supportive in so many ways. I guess maybe I should start by

acknowledging those that I’m sure to forget further on: you deserve my

fullest gratitude as well as my most humble apology. Also, I do apologize for

this utterly unsophisticated and extensive acknowledgements section, if my

(ab)use of the English language bothers you (which it probably should),

please skip it; I promise that the rest of the thesis is much more eloquent.

OK, moving on...

Lars, I am really happy with the relationship that we’ve built up over the

past 6 years. I think that from the first moment we were on a very similar

wavelength regarding many things and have become even more in phase

over the years. I am also very happy with the type of ‘supervision’ that I

received from you: lots of hands-on support initially when I needed it; lots of

independence later on when I appreciated that; always supportive to my

random whims —whether to take an extra day off for yet another frisbee

tournament or apply to a $10.000 course with a deadline in 2 days; you were

always ok with it. I also very much appreciate the personal connection that I

think we had from the beginning. I have enjoyed immensely working with

and for you and couldn’t have asked for a better PI.

Yet, everyone in the EpiLab has been an amazing and fruitful

collaborator over the years. Ana, it’s awesome to have a great buddy like you

in the lab. I love our (many many) coffee breaks with random jumps from

tedious boring discussions of antibody dilutions to tales of last weekend’s

drinking bouts and bitching sessions about [....CONFIDENTIAL

INFORMATION...]. Filipa, it has been an absolute pleasure working with you. I

could not have asked for a better student and if you have learned even half

as much from me as I have from you, then I would be as proud of myself as I

am of you. Mariana, thanks for welcoming me to the lab and to the country

from the very beginning. I very much appreciated the heated arguments and

v

the cold beers that we often shared. Luís, thanks dude, it was really fun

having you around for a while. Mariluz, Maxi, Dragan, Nuno, it has been

great having worked with all of you; Ruben, Sreyoshi, Wojtek, I wish you all

the luck in the EpiLab and am sorry we have only barely had an opportunity

to work together.

Still missing one EpiLabber, right...: João, I know that you always say

that you’re just doing your job —and you probably actually really feel that

you do— but you do so much more. Whenever needed, whatever’s the

matter, you are always ready to be as helpful as humanly possible! Whether

it is to drop me off at the airport, fix my computer over the weekend, lend

me your car for random errands, or discuss for a few hours a single sentence

of some random translation I need for some obscure reason, I know I can

always count on you. And then I won’t even mention the immense help you

are in the lab, which one could potentially argue (although I personally

wouldn’t) is indeed part of your job. Please know that all this, as well as your

friendship over the last years, is and always has been very much appreciated.

Hangout-clan, thanks a whole frickin’ bundle for sharing the joys (not

many) and pains of thesis writing. The countless screens we’ve shared as

well as the p*** that we didn’t was instrumental in pulling me through and I

hope it’s been as useful for you too. Ewa, thanks for your patience, advice,

and help about the tedious details of putting together a representable thesis.

Also thanks to the theses of Babs, Ewa, Ines, Mariana, Mariluz, and Matilde

for being great examples of what my boekje should look like.

I would also like to thank the IGC for having been a great host

institution. The open-lab philosophy and highly interactive atmosphere

created here has been extremely stimulating and productive for both work

and social purposes. A special thanks goes to everyone that has passed

through the Zheng-Ho wing and to the cell cycle club and chromatin club

communities. Nuno, the first sentence you said to me when you saw me —

“what do you think you’re doing” — and the resulting collaboration has been

one of the most influential events of my entire PhD, although one of the few

vi

things that may parallel it was the microscopy course you organized, which

taught me to think like a microscope. Alekos, Mónica, Jorge, Raquel, thanks

for the many fruitful discussions we’ve had about my projects. I am also very

much indebted to everyone at the 2012 Physiology course for having

reshaped my way of thinking about scientific problems and solutions.

Thanks also to Élio for getting me out of a pickle: I was really reluctant to sit

it out and your help was probably the one thing that could’ve and did rescue

me. Indeed, my mind reels with appreciation of what it means to have been

able to do a PhD at ITQB.

Tons of thanks also go to all the people that made my time in Portugal

and at IGC soooooo much fun for such a long time. An incomplete list could

be (in alphabetical order): Ana, Babs, Cláudia, Ewa, Filipa, Inês, Jess, João,

João Beer, Jordi, Jorge, Krzys, Laura, Lars, Luís, Mada, Marc, Mariana,

Mihailo, Nicole, Nuno, Pol, Roksana, s, Stefan, Tiago. Also lots of thanks to

everyone who has kept on throwing discs at me to keep me sane all this time,

especially Sof, Trick, Patrão, Carla, Cons, Rui, Fred, Rui, Pifre, Inês, Seb,

Morris, and of course Filipa who introduced me to this all.

ZZ, KJAJBDTK!

Natuurlijk gaat er ook onwijze dikke dank naar al mijn lieve vrienden,

ex-collega’s en mentoren thuis, die mij na al die lange jaren hopelijk nog niet

vergeten zijn. Sander, Adri, Matilde (en alle anderen waarmee ik in Sander’s

lab gewerkt heb); Paulien, Stan en Veronica; jullie hebben stuk voor stuk op

een onmiskenbare manier bijgedragen aan de vorming van de

wetenschapper die ik vandaag ben, en ik herken in mezelf nog steeds de

specifieke invloed van ieder van jullie. Piet, Petertje, Matthia, it has been a

joy and honor om samen met jullie biologisch grootgebracht te worden: onze

tijden van SPI___RAAL, ik spreek Oebli-Oebli en in je broek waren

onmisbaar om mij de biloloog te maken die ik vandaag ben. Sanne, Ditte,

Banafsheh (waarschijnlijk de enige 3 buiten mijn familie waarvan ik ervoor

zorg dat ik elke keer dat ik in Nederland ben minstens een klein beetje tijd

vind om bij te kletsen): hoera!

vii

“About 99% of everything you hear is untrue.” I think that this single

sentence, which I was told probably around age 9, instantaneously

transformed me into a scientist. Peter, you probably don’t even remember

saying this to me, but I will never forget (at least, well, I haven’t forgotten it

yet).

(MaPaDaNo(SaToMi)); Worte fehlen mir... ausser: Danke für alles!

Kommt noch eine Person die ich noch nicht gennant habe: Papa, ich

widme dir diese Dissertation. Ich glaube es gibt niemanden auf der Welt der

einen grösseren Einfluss auf meine Bildung, in jeder möglichen Hinsicht,

gehabt hat. Papa, es tut mir schrecklisch leid das du nicht hast sehen können

was aus mir geworden ist.

So it goes

viii

ix

List of Publications

In chronological order:

Silva MCC, Bodor DL, Stellfox ME, Martins NMC, Hochegger H, Foltz

DR & Jansen LET (2012) Cdk activity couples epigenetic centromere

inheritance to cell cycle progression. Dev. Cell 22: 52–63

Bodor DL, Rodríguez MG, Moreno N & Jansen LET (2012) Analysis of

Protein Turnover by Quantitative SNAP-Based Pulse-Chase Imaging. Curr.

Protoc. Cell Biol. Chapter 8: Unit8.8

Bodor DL, Valente LP, Mata JF, Black BE & Jansen LET (2013)

Assembly in G1 phase and long-term stability are unique intrinsic features of

CENP-A nucleosomes. Mol. Biol. Cell 24: 923–932

Bodor DL & Jansen LET (2013) How two become one: HJURP

dimerization drives CENP-A assembly. EMBO J. 32: 2090–2092

Bodor DL, Mata JF, Sergeev M, David AF, Salimian KJ, Panchenko T,

Cleveland DW, Black BE, Shah JV & Jansen LET (2014) The quantitative

architecture of centromeric chromatin. eLife Sciences 3: e02137

CHAPTER 1

General Introduction:

Epigenetics, Centromeres, and Quantitative Biology

Dani L. Bodor

Instituto Gulbenkian de Ciência, 2780-156, Oeiras, Portugal.

Epigenetics, Centromeres, Quantitative Biology

3

EPIGENETICS

Inheritance systems

Inheritance from a biological perspective is the transfer of information

from one (cell) generation to th e next. In order for a system of inheritance

to persist, a number of criteria need to be fulfilled. The bare minimal

requirement is that there is a carrier (or carriers) of information that can be

propagated through generations. In addition, to allow for sustained passage

of information into subsequent generations, the carrier needs to be

replicated in each generation. Moreover, in many cases it is important that

there is careful regulation to ensure that the correct number of heritable

units is passed on. Temporal regulation can play a role in quantitative

control so that e.g. one new unit is formed for each pre-existing one exactly

once per cell generation. In summary, the basic properties of a successful

inheritance system include: 1) propagation, 2) replication, and 3) copy-

number regulation.

Up to the early 1940s, there was a heated debate on the molecular nature

of heritability. Two opposing ideas were that either protein or nucleic acids

would be the carriers of genetic information (Deichmann, 2004). Among

other factors, the low apparent complexity of DNA led to the common notion

that genes were more likely composed of proteins. However, In the 1940s

and ‘50s a number of breakthrough discoveries were made that irrevocably

showed that, in fact, DNA was responsible for genetic inheritance.

Instrumental were experiments showing that DNA is the agent that is

responsible for the transformation of non-virulent into virulent

pneumococcus (Griffith, 1928; Avery et al, 1944), as well the famous

Hershey-Chase experiment, showing that viral DNA, but not protein, enters

the host upon bacteriophage infection (Hershey & Chase, 1952). Soon

afterwards, Watson and Crick published their breakthrough model of the

double-helical structure of DNA, including the now famous statement “it has

not escaped our notice that the specific pairing we have postulated

Chapter 1

4

immediately suggests a possible copying mechanism for the genetic

material” (Watson & Crick, 1953a). Indeed, the semi-conservative ‘copying

mechanism’ that was intended, where each of the two existing strands of

DNA form the template for a nascent strand (Figure 1.1A), was later

confirmed by Meselson & Stahl (1958) in what is often called ‘the most

beautiful experiment in biology.’ Much later, and over the course of decades,

the regulation mechanisms were elucidated, which ensure that the entire

genetic complement is replicated exactly once per cell division, such that

there is no under- or overduplication of the genetic material (Sclafani &

Holzen, 2007). In short, once per cell division cycle, a defined number of

replication origins are licensed with an initiation complex that is consumed

when DNA replication begins at this site, thus ensuring that the same stretch

of DNA is not replicated more than once. In addition, progression of cell

division is halted until a complex machinery, called a checkpoint, has

ensured that DNA replication is complete. In conclusion, although some

details may still need to be resolved, a fairly good understanding of the

mechanism of genetic inheritance has emerged.

As is clear from the section above, DNA perfectly fits all criteria given

above for the carrier of heritable information. This molecule is stably

propagated when cells divide, it is replicated after each cell division, and

regulated such that each molecule gives rise to only one new molecule

exactly once per division. Thus, genetic inheritance is a showcase model of

an effective inheritance system.

Non-genetic inheritance

Ever since the discovery that DNA was the carrier of genetic information,

the study of inheritance from a biological perspective has been dominated by

DNA and its nucleotide sequence. This system is perfectly able to account for

Mendel’s laws of inheritance (Mendel, 1866) as well as some more complex

variations of these principles, which together govern inheritance of the

majority of traits in sexually reproducing organisms. However, certain


5

heritable features do not strictly dependent on the genetic code of a cell. This

is most apparent from the fact that within a single multicellular organism

there can be many different cell types with the exact same genetic material.

Generally, when cells that have acquired a certain developmental status

divide, they give rise to the same cell type, e.g. a dividing skin cell will not

suddenly give rise to a heart muscle cell, and vice versa. In addition to such

non-genetic inheritance that is contained within a single organism, a

number of transgenerationally inherited traits have been described that do

not seem to follow the typical laws of inheritance. One famous example is

‘helmet’ size in the waterflea Daphnia cucullata: if exposed to a predator,

the size of this protective structure is altered throughout multiple

generations (Agrawal et al, 1999), even in the absence of a predatory cue in

the offspring. Another well-known case is the toadflax Linaria vulgaris that

exists in two distinct heritable morphological states, but can spontaneously

switch between generations without any apparent mutations in the

responsible gene (Cubas et al, 1999). Thus, there must be other structures

present in cells that are able to carry information from mother to daughter

cells, or even through organismal generations. Below, some typical examples

of alternative inheritance systems, and their method of transferring

information, are discussed.

Self-sustaining loops

Perhaps the simplest possible form of (non-genetic) inheritance is a self-

sustaining loop (Figure 1.1B). If the expression of a gene is driven by its own

product (protein or RNA), then the cytoplasmic inheritance of this factor

during cell division will ensure that the active state of the gene will also be

inherited (Rosenfeld, 2011). Gene products can either drive such feed-

forward loops directly (e.g. a transcription factor that activates the gene by

which it is produced), or, more commonly, indirectly (e.g. a protein that

initiates a genetic cascade, ultimately leading to its own expression). In

either case, gene-activity will effectively be maintained throughout

generations until it is actively (or spontaneously) interrupted. This type of

Chapter 1

6

self-sustaining loop is common in bacteria and other unicellular organisms

(Santillan et al, 2007; Jablonka & Raz, 2009), and likely contributes to the

maintenance of cell identity in multi-cellular organisms as well (Hobert,

2011; Holmberg & Perlmann, 2012; Ptashne, 2013).

Figure 1.1 Examples of inheritance systems. (A) DNA is replicated in a semiconservative fashion. During replication, a

single DNA duplex untwines and individual nucleotides on each strand form the template for production of a new strand

of DNA (image adapted from: The Nucleus and DNA Replication, 2015). (B) Once initiated by an external cue (indicated

by a bomb), gene products that maintain their own expression through a self-sustaining loop can be inherited through

the cytoplasm during cell division. In this way, they maintain their activity in the next cellular generation, even in the

absence of the original initiating signal (image adapted from: Jablonka & Lamb, 2006). (C) Prion transmission is an

example of structural inheritance. The amyloid protein conformer (red) catalyzes conversion of native protein isoforms

of identical amino acid sequence (blue balls) into its own conformation (image adapted from: Shorter & Lindquist,

2005). (D) DNA methylation is the best understood form of chromatin-based epigenetics. DNMT3 is a de novo

methyltransferase that is capable of adding methyl groups (red hexagons) to cytosines on unmethylated DNA. During

DNA replication, the maintenance methyltransferase DNMT1 associates with the core replication machinery and

specifically methylates hemimethylated DNA, thus retaining the pre-replication methyl-pattern in the next generation.

Conversely, TET enzymes can oxidize methylated cytosine into hydroxymethylcytosine (orange hexagons), which can

initiate a pathway that restores unmethylated DNA (image adapted from: Li & Zhang, 2014).


7

In this inheritance system, the carrier of heritable information is the

gene product (let’s call it Factor X). Factor X is propagated through the

cytoplasm of a dividing cell, oftentimes by random segregation of the total

pool of existing molecules (Rosenfeld et al, 2005). Replication in the next

generation is achieved by activating the gene that is responsible for

producing Factor X. Although in this case there is no absolute requirement

for copy number regulation with a high degree of accuracy, sufficient

molecules are required to ensure that each daughter sustains and

perpetuates gene activity. In summary, self-sustaining loops represent a very

basic example of a stable inheritance system.

Structural inheritance

In some cases, a given three dimensional structure propagates itself by

forming the template for assembly of the same structure. Perhaps the most

elegant (and best understood) structural inheritance system is in fact genetic

inheritance, where nascent strands of DNA are templated onto existing

molecules (Watson & Crick, 1953a, 1953b; Meselson & Stahl, 1958).

However, many additional structural inheritance systems have been

described. A clear example are prions (Figure 1.1C), proteins of identical

amino-acid sequence that can exist in multiple conformational states, at

least one of which drives conversion of the other(s) into itself (Prusiner,

1982, 1998; Halfmann et al, 2010). Although prions are generally considered

detrimental or pathogenic, it has been shown that they can have a

physiological role by conferring advantageous traits in certain environments

(Halfmann et al, 2010, 2012). Prion inheritance is in many ways analogous

to the self-sustaining loops described above (it is itself a type of feed forward

loop), as it is inherited through the cytoplasm where it will replicate by

mediating a nascent protein isoform into its own conformational state.

An interesting case is presented by the centrosome, the primary

microtubule organizing center (MTOC) in most animal cells. A single

centrosome contains two centrioles, cylindrical structures composed mainly

Chapter 1

8

of tubulin, each of which nucleate a nascent daughter centriole exactly once

per cell division cycle (Bettencourt-Dias & Glover, 2007; Nigg & Stearns,

2011). Conversely, centrioles can also form de novo under certain

conditions, although this is strongly suppressed be the presence of pre-

existing centrosomes (Marshall et al, 2001; Terra et al, 2005; Rodrigues-

Martins et al, 2007). However, this inheritance mechanism differs from true

structural inheritance, as there is no evidence for actual templating of one

centrosome against another. Rather, centrosomes are more likely sites

where enzymes, regulatory, and structural proteins accumulate to regulate

the biogenesis of nascent structures (Rodrigues-Martins et al, 2007, 2008),

allowing for a semi-conservative replication mechanism that is carefully

regulated by the cell cycle (Bettencourt-Dias & Glover, 2007; Nigg &

Stearns, 2011). In this system, the carrier of heritable information are the

centrioles, although it is not completely clear what the information is that

they carry. Nevertheless, their replication is strictly regulated in time, space,

and number to ensure the propagation of the correct number of structures to

the following generation.

Other examples of structural (or structural-like) inheritance systems

include the organization of ciliary rows on the cell cortex of certain ciliates

(Sonneborn, 1964), cellular membranes (Cavalier-Smith, 2004), certain

organelles (Warren & Wickner, 1996), or even the cell as a complete entity.

In summary, structural inheritance is a common mechanism to pass

information from one generation to the next.

Chromatin-based epigenetics

The term epigenetics was originally coined by Conrad Waddington in

1942 to indicate “the mechanism by which the genes of the genotype bring

about phenotypic effects” (Waddington, 1942). In this definition, epigenetics

does not refer to any heritable features, but is more similar to what today is

considered gene regulation or developmental biology. However, throughout

the last 70-odd years, the word epigenetics has been used and redefined in


9

many different ways (Jablonka & Lamb, 2002; Bird, 2007; Marris et al,

2008). One very broad definition of an epigenetic phenomenon is: “a change

in phenotype that is heritable but does not involve DNA mutation”

(Gottschling, 2004). However, if taken literally, this definition encompasses

certain heritable features that are usually not intended, such as traits

acquired through social learning (Jablonka & Lamb, 2005; Shea, 2009) or

vertically transmitted infections and symbionts (Ford-Jones & Kellner,

1995; Moran et al, 2008). Nevertheless, more recently, during a conference

on chromatin-based epigenetics at Cold Spring Harbor, a consensus

definition was formulated as: “a stably heritable phenotype resulting from

changes in a chromosome without alterations in the DNA sequence” (Berger

et al, 2009). Perhaps unsurprisingly, this consensus definition only includes

what the main topic of the conference was, namely chromatin-based

epigenetics (see below), while excluding all other potential forms of

epigenetics, including self-sustaining loops and structural inheritance. In my

own opinion, the most useful definition of epigenetic inheritance goes along

the lines of: information that cells can pass to their progeny without

changing their DNA sequence (paraphrased from Jablonka & Lamb, 2005,

p. 113). In this case, heritable features at the cellular molecular scale (e.g.

self-sustaining loops and structural inheritance) are included, while features

heritable at the organismal scale (e.g. symbiosis and learning) are not.

Deceptively, yet more definitions exist outside of biology, e.g. epigenetic

robotics, which is related to machine learning (Prince & Demiris, 2003), and

the epigenetic theory of human development, a psychological theory of

transitions in human development through psycho-social crises (Erikson,

1950). Therefore, although I only partially agree, Adrian Bird makes a

reasonable point when he says: “epigenetics is a useful word if you don't

know what's going on — if you do, you use something else” (Marris et al,

2008).

Despite the ongoing controversy on the exact meaning of epigenetics,

practically speaking, chromatin-based epigenetics is the most actively

Chapter 1

10

studied form of non-genetic inheritance. The structure and organization of

chromatin allows for a plethora of modifications, many of which can either

be inherited or participate in a pathway that drives inheritance. In addition,

this complex nature of chromatin allows for tight control of the transmission

of the epigenetic signal. I will first proceed with a brief introduction on

chromatin and then delve deeper into its role in epigenetic inheritance.

Chromatin structure

Generally, the existence of chromatin is attributed to the necessity of

fitting a large (eukaryotic) genome into a much smaller nucleus. If we take

human cells as an example, the total length of the 46 chromosomes, together

comprising over six billion base pairs of DNA, would exceed two meters if

placed head-to-tail (Flicek et al, 2014). However, in analogy to packing a

suitcase, it does not make much sense to lay all ones clothes in a neat line

next to other and then wonder how this will ever fit into a small carry-on bag

(Morse, 2013). Similarly, chromosomes are not linearly extended molecules,

but are folded and packaged into three-dimensional structures. In fact, the

paradox of fitting 2 meters worth of DNA into an average sized nucleus of ~7

μm in diameter is easily resolved by the fact that the volume of this nucleus

is almost 30 times as big as that of the total DNA (respective volumes ~180

μm3 and ~6.3 μm3). Thus, chromatinization is a means of proper folding of

the DNA, and has additional roles in organizing and regulating the genome.

The primary organizational unit of chromatin is the nucleosome

(Kornberg, 1974; Olins & Olins, 1974). A single nucleosome consists of ~145

bp of DNA tightly wrapped around an octamer consisting of two copies of

each of the histone proteins H2A, H2B, H3, and H4 (Luger et al, 1997). The

octamer itself is composed of a central (H3/H4)2 tetramer, flanked by two

H2A/H2B dimers. These core histones are among the most highly conserved

eukaryotic proteins (Sullivan et al, 2000, 2002; Malik & Henikoff, 2003),

arguing that little structural variability is tolerated for their function. This is

especially true in their histone fold domain (HFD), which form the major


11

interactions between the separate histones as well as with the DNA (Luger et

al, 1997) and are 100% identical between human and certain plants and

fungi (Sullivan et al, 2002). Histone H1 serves as a linker-histone, which

binds DNA between neighboring nucleosomes, thereby helping to stabilize

the chromatin structure (Thoma et al, 1979). Further organization is likely

achieved by multiple forms of higher order structures, the precise in vivo

nature of which has proven to be very challenging to determine (Woodcock

& Ghosh, 2010). Despite the high level of conservation and strong

interaction of the histone-DNA binding, chromatin is both a heterogeneous

and a dynamic structure (Gasser, 2002; Flaus & Owen-Hughes, 2004;

Chakravarthy et al, 2005). Indeed, both replication and transcription

machineries displace, reorganize, and remodel the nucleosomes as DNA and

RNA polymerases, respectively, plough through the chromatin (Mousson et

al, 2007; Groth et al, 2007). In addition, certain regions of the chromosome

can be highly compacted, while flanking regions remain accessible to

external factors, such as transcription factors or other DNA binding proteins

(Wu et al, 1979; Larsen & Weintraub, 1982; Song et al, 2011). Furthermore,

major rearrangements of this chromatin organization commonly occur, e.g.

throughout the cell cycle (Reeves, 1992; Aragon et al, 2013; Raynaud et al,

2014) and during cell differentiation (Meshorer & Misteli, 2006;

Kobayakawa et al, 2007; Probst & Almouzni, 2008). In summary, while

composed of fairly simple units, chromatin is a highly complex structure

that is regulated at the level of configuration, organization, and dynamics.

Consistent with its complexity, a large variety of processes exist that help

effectively regulating chromatin homeostasis and dynamics in cells. The

close association of chromatin and its modifications to the genome of the

cells makes it an excellent candidate for driving epigenetic inheritance, e.g.

of gene activities. Three of the major mechanisms are DNA methylation,

incorporation of histone variants, and modification of histone proteins. Each

of these processes has the potential, supported at least by some evidence, to

drive epigenetic inheritance, and will be briefly discussed below.

Chapter 1

12

DNA methylation

DNA methylation, the covalent addition of a methyl group to the DNA

backbone, is found throughout the tree of life (Colot & Rossignol, 1999;

Jeltsch, 2002; Ponger & Li, 2005). However, this modification was lost

multiple times in evolution, and is absent from a wide variety of species

including D. discoideum, S. cerevisiae, S. pombe, and C. elegans (Ponger &

Li, 2005). Methylation of DNA can affect many cellular processes, including

gene-regulation, transposon silencing, heterochromatin formation, and

susceptibility to restriction enzymes, depending to some extent on the

species (Colot & Rossignol, 1999). In eukaryotes, methylation at carbon 5 in

the pyrimidine ring of cytosine, thus creating 5-methylcytosine (meC), is the

only known form of methylated DNA (Jeltsch, 2002). In plants, any cytosine

in the genome has the potential to be methylated, although separate

enzymes are responsible for the methylation of CG-dinucleotides (CpG),

CHG-sites (where H is any non-guanine nucleotide), and CHH-sites (Law &

Jacobsen, 2010). In mammalian cells, however, DNA methylation is largely

restricted to CpGs (Sinsheimer, 1955), although low levels of meC can be

observed on other sites, especially in germ and stem cells (Ramsahoye et al,

2000; Ichiyanagi et al, 2013). Importantly, not every potential site is

methylated, e.g. ~14% of cytosines are methylated in Arabidopsis thaliana

leaf tissue (Capuano et al, 2014), while ~70–80% of CpGs are methylated in

somatic human tissues (Ehrlich et al, 1982; Bird, 2002). Furthermore, the

pattern of methylation can differ between different cell types of the same

organism and change during differentiation (Reik et al, 2001). Thus,

sequence determinants are not sufficient to explain the existing pattern of

DNA methylation.

The vast majority of meC sites in the mammalian genome are

symmetrically methylated. In other words, either both strands of a

minipalindromic CpG site are methylated, or neither is (Bird, 1978).

However, the process of DNA replication inevitably leads to the formation of

hemimethylated DNA, where a nascent strand of unmethylated DNA is


13

templated against a methylated pre-existing strand. The DNA

methyltransferases DNMT1 has been shown to have a high preference for

hemimethylated DNA (Bestor & Ingram, 1983) and associate with the core

DNA replication machinery protein PCNA (Chuang et al, 1997) as well as

with NP95, which specifically recognizes hemimethylated DNA (Sharif et al,

2007). In this way, DNMT1 is accurately targeted to hemimethylated DNA

during its formation and can restore the pre-existing pattern of methylation.

This shows that DNA methylation is a semiconservatively inherited

epigenetic feature and intrinsically coupled to cell cycle regulation (Figure

1.1D).

Although DNA methylation is generally considered a stable epigenetic

modification, its genomic pattern is largely reset in each generation.

Demethylation can potentially occur in two fundamentally different ways.

One is the passive dilution of meC during successive rounds of DNA

replication in the absence of maintenance methylation. The other is by

active removal of methylated cytosines, although claims of finding such

mechanisms have a history of being highly controversial (Ooi & Bestor,

2008). Only recently has a bona fide active demethylation pathway been

described, where meC is iteratively oxidized into hydroxymethylcytosine

(Tahiliani et al, 2009), formylcytosine, and carboxylcytosine (Ito et al, 2011;

He et al, 2011), the latter two of which can be converted back to unmodified

cytosine through base-excision repair (He et al, 2011; Maiti & Drohat, 2011).

This pathway may explain how, in the absence of replication, methylated

DNA is rapidly lost from the mouse paternal pronucleus after fertilization

(Mayer et al, 2000; Oswald et al, 2000). Embryonic stem cells re-initiate a

nascent pattern of DNA methylation (Jähner et al, 1982; Stewart et al, 1982)

using the de novo DNA methyltransferases DNMT3a and DNMT3b (Okano

et al, 1998, 1999). However, a recent analysis on the genome-wide

methylation patterns of three great apes, including human, argues that

methylation patterns can gradually change over generations and may

ultimately even contribute to variability between species (Martin et al, 2011;

Chapter 1

14

Boffelli & Martin, 2012). Nevertheless, generally speaking, it appears that

DNA methylation in mammals is mainly involved in epigenetic inheritance

through mitotic divisions, and has a relatively minor role in

transgenerational inheritance.

Histone variants

As mentioned above, canonical nucleosomes contain a histone octamer

consisting of four different types of histone proteins: H2A, H2B, H3, and

H4. Multiple different variants exist for each of these histone proteins in

most species analyzed (Talbert et al, 2012), with the exception of H4, for

which a sole known non-canonical variant exists in Trypanosoma (Siegel et

al, 2009). In humans, up to 47 non-allelic variants, i.e. proteins with

different amino acid sequence, have been described in total for the four

nucleosomal histones (Wiedemann et al, 2010; Khare et al, 2011). However,

it remains unclear whether each variant actually has distinct properties,

especially in cases with only one or few residues divergence. Nevertheless,

one example where this is indeed the case is histone H3.3, which differs

from its canonical H3.1 counterpart by a mere 5 amino acids, yet its

dynamics and regulation are drastically different. H3.1 is assembled

throughout the genome by the CAF complex in a strictly DNA replication-

coupled manner, while H3.3 assembly occurs preferentially at specific loci

by the histone chaperones HIRA, DAXX, and DEK and is independent of the

cell cycle (Smith & Stillman, 1989; Ray-Gallet et al, 2002; Ahmad &

Henikoff, 2002; Tagami et al, 2004; Drané et al, 2010; Goldberg et al, 2010;

Sawatsubashi et al, 2010). Therefore, altered histone variant compositions

of the nucleosome are good candidates as carrier of epigenetic information.

The process of DNA replication forms an inherent challenge to the local

heritability of histones. In order for a megadalton sized replication complex

to pass through the chromatin, nucleosomes are disassembled prior to the

denaturation and replication of DNA (Groth et al, 2007; Alabert & Groth,

2012). However, pre-existing subnucleosomal (H3/H4)2 tetramers are


15

recycled behind the replication fork, possibly through their association with

the histone chaperone Asf1 (Groth et al, 2007; Mousson et al, 2007; Alabert

& Groth, 2012). Conversely, it appears that histones H2A and H2B are more

dynamic than H3 and H4 (Jackson, 1987; Kimura & Cook, 2001; Bodor et al,

2013) and thus less likely to carry epigenetic information. Consistently,

evidence exists that at least two variants of histone H3 are carriers of

epigenetic information. The role of the centromeric variant CENP-A is

described in detail in part 2 of the introduction. The replacement variant

H3.3 is enriched at sites of high gene activity (Ahmad & Henikoff, 2002;

Mito et al, 2005; Goldberg et al, 2010), and is enriched in post-translational

modifications associated with active transcription (McKittrick et al, 2004;

Hake et al, 2006). Importantly, it has been shown that H3.3 is involved in

the resistance to reprogram an active gene expression profile in Xenopus

after transplantation of somatic cell nuclei into oocytes (Ng & Gurdon,

2008). Interestingly, a similar role for macroH2A was found by maintaining

a repressed state on the X-chromosome (Pasque et al, 2011) and on

pluripotency genes (Gaspar-Maia et al, 2013). Although the precise mode of

action of these histone variants remains unclear, it appears that they are

somehow involved in the transmission of an epigenetic state.

Histone modifications

In addition to modifying the histone variant composition of

nucleosomes, each of the histones can undergo a large number of post-

translational modifications (PTMs). Common modifications on histones

include acetylation, methylation, phosphorylation, ubiquitylation,

citrullination, biotinylation, and ADP-ribosylation (Khare et al, 2011). Most

PTMs exist in the protruding N-terminal histone tails, while only few are

found within the HFD (Khare et al, 2011). In some cases, a single residue is

known to exist in multiple different modified forms; e.g., lysine 9 of Histone

H3 (H3K9) can be mono-, di-, or trimethylated, acetylated, or biotinylated.

Indeed, on histone H3 alone, there are at least 44 separate known

modifications, spread over 21 individual sites, resulting in over three billion

Chapter 1

16

potential combinatorial states of modification on each molecule (Khare et al,

2011). Interestingly, many modifications are shown to correlate with specific

(functional) states, such as high or low gene-activity, splicing, DNA repair,

and DNA replication (Bannister & Kouzarides, 2011). These findings have

spurred the hypothesis of a ‘histone code’ that can be read by downstream

effector proteins or have a function in epigenetic memory (Strahl & Allis,

2000; Jenuwein & Allis, 2001; Turner, 2002; Rothbart & Strahl, 2014).

However, because most PTMs are not exclusively associated with any one

particular state (Barski et al, 2007), such a histone code can at best be seen

as a highly complex combinatorial code or language (Lee et al, 2010;

Rothbart & Strahl, 2014), unlike e.g. the linear genetic code (1 codon => 1

amino acid). Nevertheless, similar to histone variants, PTMs on histone tails

have the potential to propagate epigenetic information.

PTMs are often equated to epigenetic marks, even in the scientific

literature (e.g. Turner, 2002). However, in many cases there is clear

evidence that the PTMs are not inherited at all, but are transient structures

that mediate e.g. cell cycle progression (Van Hooser et al, 1998), DNA

replication (Benson et al, 2006), or DNA repair (Rogakou et al, 1999; Hunt

et al, 2013). In addition, for many modifications that are associated to gene-

activity, it remains unclear whether they are the cause or consequence of the

transcriptional state (Ng et al, 2003; Soshnikova & Duboule, 2009;

Muramoto et al, 2010). Nevertheless, while, at least to my knowledge, there

is no direct evidence that PTMs carry and transmit epigenetic information,

they remain strong candidates at least for certain modifications.

Epigenetics in evolution

Above, it has been thoroughly established that heritability is not

exclusively mediated by the genome. Although most examples given refer

mainly to inheritance of features through mitotic divisions, i.e. within the

somatic cells of a single organism, more than 100 examples of trans-

generational epigenetic inheritance from 40 different species have been


17

documented by Jablonka & Raz (2009). Given this wealth of epigenetic

heritability, at least some of the traits must be adaptive and advantageous

phenotypes to certain environments have been observed for variable

methylomes in the plant species Arabidopsis thaliana (Johannes et al,

2009) and Mimulus guttatus (Scoville et al, 2011), as well as prions in S.

cerevisiae (Halfmann et al, 2012), heritable antiviral RNA molecules in C.

elegans (Rechavi et al, 2011), and gene silencing in D. melanogaster (Stern

et al, 2012). Together, these observations lead to the interesting possibility

that non-genetic inheritance can contribute to evolutionary dynamics.

To illustrate that evolution can be driven by epigenetic inheritance,

Jablonka and Lamb (2005) used an interesting thought-experiment

approximately along the following lines:

Imagine a faraway planet that is as rich and dynamic a world as our own, featuring

many different environments and climates; let’s call it CB (for Complex Biosphere). This

world is inhabited by a population of creatures that does not tolerate any divergence in its

genome whatsoever; let’s call them SAM (for Species in the Absence of Mutation). Given

the richness of the environment, there is a great potential for SAM to adapt to many

different niches. Therefore, as time goes by, SAM plays it (again) in a way that does not

require any genetic change. Rather, SAM differentially produces epigenetic traits, e.g.

through altering the gene methylation states, generating novel prion-like protein con-

formations, or activating self-sustaining loops. If advantageous in a given milieu, adapted

individuals will prosper, compete more successfully for the available resources, and

produce a higher number of offspring. Thus, by means of natural selection, the epigenetic

diversification of SAM in different environments will ultimately be the origin of species.

Given that imagination is the only weapon in the war against reality, we

do not want to argue here that actual evolution is driven solely by epigenetic

changes. Nevertheless, this story does clearly make the point that

adaptation, and thus evolution, can in principle occur through inheritance of

variable, non-genetic traits. Accepting that “variations, however slight and

from whatever cause proceeding, if they be in any degree profitable to the

individuals of a species [...], will tend to the preservation of such

individuals” (Darwin, 1859: p.61; emphasis mine), it is difficult to imagine

that natural selection would not work on epigenetically inherited traits.

Chapter 1

18

The influence of epigenetic mechanisms on evolution could be very

different from genetic inheritance. Importantly, reproduction of epigenetic

states in the next generation is generally much less accurate than genetic

inheritance. For example, while DNA replication occurs at an error rate in

the range of ~10-6–10-8 (Kunkel, 2004), errors in copying DNA methylation

occur as frequently as ~0.3–4% (Laird et al, 2004; Goyal et al, 2006).

Although a higher error rate likely makes epigenetic traits less stable, it may

also lead to a more rapid acquisition in response to changing environments

(Cubas et al, 1999; Pryde & Louis, 1999). These and other epigenetic specific

effects (Jablonka, 2012) make that the classical models of evolution and

population dynamics need to be reevaluated. However, only recently have

different aspects of epigenetics started to be integrated in such models (Tal

et al, 2010; Day & Bonduriansky, 2011; Geoghegan & Spencer, 2012). In

addition, epigenetic mechanisms have been proposed to have a role in

speciation, macroevolution, and even the major transitions in evolution

(Jablonka & Lamb, 2006; Jablonka & Raz, 2009; Boffelli & Martin, 2012;

Jablonka, 2012).


19

CENTROMERES

The function of centromeres

Centromeres were originally defined cytologically by Walther Flemming

in the late 19th century, as the site of a ‘primary constriction’ in mitotic

chromosomes (Flemming, 1880). Today, we have a fairly good

understanding of what brings about this particular structure. During DNA

replication, nascent sister chromatids are held together by a protein complex

called cohesin (Figure 1.2A), thus preventing precocious separation and

chromosome missegregation (Michaelis et al, 1997; Uhlmann & Nasmyth,

1998). Upon entry into mitosis (or meiosis), the chromosomes condense

(Koshland & Strunnikov, 1996) and the majority of cohesin is removed from

the chromosomes (Losada et al, 1998). However, cohesin is preferentially

retained at a single site on each sister chromatid pair, the centromere

(Losada et al, 2000; Waizenegger et al, 2000), where it is protected by

Shugoshin proteins (Kerrebrock et al, 1995; Salic et al, 2004). Only when

cells are ready to exit mitosis and segregate sister chromatids to the

daughter cells is the remaining centromeric cohesin cleaved by a protein

called separase (Uhlmann et al, 1999, 2000). Thus, centromere specific

cohesion is responsible for the X-shaped conformation of mitotic

chromosomes and Flemming’s primary constriction (Haarhuis et al, 2014).

Centromeres are also the chromosomal loci that form the point of

contact between the DNA and the mitotic spindle (Figure 1.2B). A large

group of proteins, the constitutive centromere associated network (CCAN),

are present at the centromere throughout the cell cycle (Foltz et al, 2006;

Izuta et al, 2006; Cheeseman & Desai, 2008). During mitosis, the CCAN

recruits a secondary protein complex known as the kinetochore, which

includes the conserved microtubule-binding KMN network, consisting of the

protein KNL1 as well as the Mis12 and Ndc80 complexes (Cheeseman et al,

2004, 2006; DeLuca et al, 2006). Poleward directed pulling forces are

exerted on centromeres by stable binding of depolymerizing microtubules at

Chapter 1

20

kinetochores, which drag the sister chromatids in opposite directions during

anaphase (Brinkley & Cartwright, 1975; Salmon et al, 1976; Mitchison et al,

1986; Inoué & Salmon, 1995). Thus, the centromere is the primary structure

responsible for recruiting the entire chromosome segregation machinery.

Figure 1.2 Centromeres control chromosome segregation. (A) Sister chromatid cohesion is maintained specifically at

centromeres during mitosis to prevent precocious chromosome separation (image adapted from: Nasmyth & Haering,

2009). (B) During mitosis, centromeres form a recruitment hub for kinetochores, including the microtubule binding

Ndc80 complex, which drive chromosome segregation during anaphase (image adapted from: Cheeseman & Desai,

2008). (C) An Aurora B gradient emanating from the inner centromere destabilizes proximal kinetochore-microtubule

interactions to prevent asymmetric chromosome segregation (image adapted from: Lampson & Cheeseman, 2011).


21

Finally, centromeres have an integral role in monitoring proper

kinetochore-microtubule interactions. The formation of amphitelic

attachments, where sister centromeres are attached to microtubules of

opposing spindle poles, guarantees that chromosomes are pulled in opposite

directions during anaphase (Cimini et al, 2001). The spindle assembly

checkpoint (SAC), aka the mitotic checkpoint, is recruited to centromeres at

the onset of mitosis (Chen et al, 1996; Li & Benezra, 1996) and monitors the

attachment status of centromeres (Sacristan & Kops, 2015). Attachment of

microtubules to the kinetochore allows for the active removal of SAC

proteins from the centromere (Waters et al, 1998). However, kinetochore-

microtubule interactions are destabilized by the Aurora B kinase (Figure

1.2C)., localized in between the sister centromeres, in a distance dependent

manner often called the Aurora B gradient (Pinsky et al, 2006; Liu et al,

2009). Only upon formation of amphitelic attachments are kinetochores

sufficiently distant from Aurora B to allow for stable microtubule

attachments. The SAC is silenced once amphitely has been accomplished on

all chromosomes, leading to the activation of APC/C, an E3 ubiquitin ligase

that marks target proteins for destruction (Hardwick & Shah, 2010).

Important targets include Cyclin B (Amon et al, 1994; Irniger et al, 1995;

King et al, 1995; Sudakin et al, 1995), which activates the mitotic master

regulator Cdk1, and securin (Zur & Brandeis, 2001), which inhibits separase

from cleaving cohesin. Thus cells are inhibited from exiting mitosis until

proper amphitelic attachments are made on all chromosomes and accurate

chromosome segregation is ensured.

In summary, centromeres play a key role in the regulation of mitotic

progression. Centromeres are responsible for maintenance of sister

chromatid cohesion, recruitment of the microtubule binding kinetochore

complex, and monitoring proper kinetochore-microtubule attachments.

Together, the concerted action of these processes allows for dividing cells to

accurately segregate their chromosomes to the two nascent daughters.

Chapter 1

22

Specification of centromere identity

Centromeric DNA

Because centromeres are chromosomal loci, the simplest possible

mechanism to specify them is by a particular nucleotide sequence. Indeed,

in the budding yeast S. cerevisiae, centromeric sequences consist of three

elements, called CDEI, CDEII, and CDEIII (for centromeric DNA element 1–

3). CDEI (8 bp) and CDEIII (25 bp) are both highly conserved between the

sixteen S. cerevisiae centromeres, and CDEII (~80–85 bp), although not

well conserved, systematically has an AT-richness of >90% (Hieter et al,

1985; Niedenthal et al, 1991; Hegemann & Fleig, 1993). Mutations in any of

these elements can cause a dramatic increase in chromosome loss, indicative

of failure to form functional centromeres (Gaudet & Fitzgerald-Hayes, 1989;

McGrew et al, 1989; Niedenthal et al, 1991; Hegemann & Fleig, 1993; Meluh

& Koshland, 1995), with the most severe effects in CDEIII, where specific

single point mutations can completely abolish centromere function

(McGrew et al, 1986). Conversely, a naïve 125 bp sequence encompassing

the three centromere elements is sufficient to operate as a functional

centromere (Cottarel et al, 1989). In summary, specific DNA sequences are

both sufficient and required for centromere function in budding yeast.

Based on the budding yeast model system, it was originally thought that

centromeres in other species would also be critically dependent on specific

DNA sequences or motifs (Willard, 1990). However, unlike budding yeast,

centromeres in most other species contain highly repetitive tandem repeat

sequences, making them muchly much much more difficult to study. In

fission yeast, for example, centromeres consist of a small complex (i.e. non-

repetitive) central core (~4–7 kbp) flanked by ~40–100 kbp of repeat

sequences (Fishel et al, 1988; Chikashige et al, 1989), while centromeric

DNA of Drosophila is characterized by 5 bp repeats, interspersed with

transposable elements (Sun et al, 1997). Human centromeres are formed by

megabase-sized stretches of so-called alpha-satellite DNA, which consists of


23

imperfect repeats of a 171 bp AT-rich sequence (Manuelidis & Wu, 1978;

Manuelidis, 1978; Willard & Waye, 1987). Surprisingly, conservation of

centromeric sequences is quite poor, even between closely related species

(Haaf & Willard, 1997; Csink & Henikoff, 1998; Malik & Henikoff, 2002; Lee

et al, 2005, 2011). In addition, it has been observed in multiple lineages that

the position of centromeres along the chromosomes can change

independently of the surrounding sequences or structural rearrangements

(Montefalcone et al, 1999; Rocchi et al, 2012). Interestingly, as was first

described in the long bug Protenor belfragei (Schrader, 1935), centromeres

are not necessarily restricted to any one locus, but can instead be diffusely

spread along the length of the chromosome in what is called a holocentric

arrangement. C. elegans is probably the best known example (Albertson &

Thomson, 1982), but holocentricity has been observed in many species and

has evolved multiple independent times in both animals and plants (Melters

et al, 2012). Given all these observations, centromeres are considered among

the fastest evolving chromosomal regions in eukaryotes (Henikoff et al,

2001), which conflicts with the hypothesis that centromere identity is driven

by a specific sequence context.

Positive evidence against DNA sequences being essential for human

centromere specification came with the discovery of centromeres on atypical

loci. So-called neocentromeres were first identified in 1993 on a stably

segregating fragment of chromosome 10 that lacked typical α-satellite or

other centromeric sequences (Voullaire et al, 1993). Although centromere

repositioning appears to be a rare event, over 130 unique human

neocentromeres, spanning all chromosomes except 22, have been found to

date (Marshall et al, 2008; Liehr, 2014). In the majority of cases analyzed,

virtually all cells (within one lineage) contained the same neocentromere,

arguing in favor of stable inheritance of the neocentric locus through mitotic

divisions (Marshall et al, 2008). Moreover, at least seven independent

neocentromeres have been described, which are inherited through human

generations (Wandall et al, 1998; Tyler-Smith et al, 1999; Knegt et al, 2003;

Chapter 1

24

Amor et al, 2004; Ventura et al, 2004; Capozzi et al, 2009; Hasson et al,

2011), arguing that they are stable in meiosis as well. Importantly, large

arrays of α-satellite sequences that did not display any centromeric function

can be retained neocentric chromosomes, including meiotically stable ones

(Bukvic et al, 1996; Tyler-Smith et al, 1999; Amor et al, 2004; Ventura et al,

2004; Capozzi et al, 2009; Liehr et al, 2010; Hasson et al, 2011). In

summary, observations on neocentromeres argue that centromeric

sequences are neither required nor sufficient for centromere specification in

human cells.

Although not strictly required for centromere identity, specific sequences

cannot be excluded to have a function. Indeed, one well known feature of

mammalian centromeric DNA is the recruitment of CENP-B, a sequence

specific DNA binding protein that recognizes a 17 bp site found within a

proportion of α-satellite monomers (Masumoto et al, 1989). Although

CENP-B is non-essential (Hudson et al, 1998), it may play a role in

organizing centromeric chromatin (Pluta et al, 1992; Hasson et al, 2011) and

it has recently been suggested to contribute to centromere function

(Fachinetti et al, 2013). Moreover, in an effort to create centromeres de novo

on human artificial chromosomes, it was found that both α-satellite DNA

and centromeric CENP-B binding sites are essential (Ohzeki et al, 2002).

Another interesting observation is that a surprisingly high number of human

neocentromeres have been found at regions that correlate with centromere

positions in other primates (Ventura et al, 2003, 2004; Cardone et al, 2006;

Capozzi et al, 2008, 2009). Moreover, it was found that orthologous loci

have been used in multiple species for evolutionary centromere

repositioning events that have become fixed in the population (Ventura et al,

2004). Together, these observations suggest that while specific sequences

are dispensable for centromere function and maintenance, they appear to

have at least some influence on de novo centromere formation.


25

CENP-A

Because DNA sequences are not responsible for centromere identity,

another defining factor must exist. Using auto-immune sera from human

scleroderma patients, centromere protein A (CENP-A) was among the first

proteins (together with CENP-B and CENP-C) to be identified at human

centromeres (Earnshaw & Rothfield, 1985). Soon after its discovery, it was

found that CENP-A has many histone-like properties and copurifies with

core histone proteins (Palmer et al, 1987). In addition, it shares sequence

homology to histone H3, which strongly suggested that CENP-A can replace

this histone in centromeric nucleosomes (Palmer et al, 1987, 1991), which

was confirmed by in vitro reconstitution studies some 10 years later (Yoda et

al, 2000). The first piece of evidence indicating that CENP-A may be the

defining feature for centromere identity came from the discovery that it is

absent from inactive centromeres in dicentric chromosomes, but readily

detected on neocentromeres (Earnshaw & Migeon, 1985; Warburton et al,

1997). In addition, clear centromere specific CENP-A homologues exist in

nearly all species analyzed (Malik & Henikoff, 2003; Talbert et al, 2012),

with the notable exception of kinetoplastids (Akiyoshi & Gull, 2013).

Surprisingly, it was recently found that multiple holocentric insects appear

to have lost CENP-A (Drinnenberg et al, 2014), although the presence of

centromere specific H3 variants not matching their criteria was not

excluded. Furthermore, loss of CENP-A is lethal and results in severe defects

of chromosome segregation in all species analyzed (Stoler et al, 1995;

Buchwitz et al, 1999; Henikoff et al, 2000; Howman et al, 2000; Blower &

Karpen, 2001; Talbert et al, 2002; Régnier et al, 2005; Black et al, 2007b).

Conversely, CENP-A is sufficient for the recruitment of virtually all known

centromere and kinetochore proteins (Foltz et al, 2006; Heun et al, 2006;

Liu et al, 2006; Okada et al, 2006; Carroll et al, 2009, 2010; Barnhart et al,

2011; Guse et al, 2011; Mendiburo et al, 2011), with the exception of the

sequence specific DNA binding protein CENP-B (Pluta et al, 1992; Voullaire

et al, 1993). Importantly, CENP-A nucleosomes are stably transmitted

Chapter 1

26

through both mitotic (Jansen et al, 2007) and meiotic (Palmer et al, 1990;

Raychaudhuri et al, 2012; Dunleavy et al, 2012) cell divisions. Together,

these observations have for many years spurred the hypothesis that CENP-A

is primarily responsible for specifying centromeric identity.

Despite these indications, direct evidence that CENP-A defines

centromere identity was lacking until very recently. In a seminal study,

Mendiburo et al (2011) used cultured Drosophila S2 cells in which they

expressed a fusion protein of CENP-ACID and LacI that can be targeted to a

chromosomally integrated LacO array. Using this cell line, the authors were

able to show that ectopically targeted CENP-ACID is assembled into

nucleosomes, recruits virtually all known Drosophila centromere and

kinetochore proteins, stably binds kinetochore microtubules, and behaves as

a functional centromere (Mendiburo et al, 2011). Most importantly, it was

shown that a substantial pool of naïve CENP-ACID, which has no intrinsic

affinity for LacO sequences, is present on the array up to 7 days after pulse-

expression of targeted CENP-ACID-LacI (Mendiburo et al, 2011). More

recently, it was shown that LacO-tethering of the CENP-A loading factor

HJURP is not only sufficient to induce neocentromere formation, but it is

also able to rescue chromosome stability and cell viability after deletion of

the endogenous centromere in chicken DT40 cells (Hori et al, 2013).

Intriguingly, this same study found similar results after tethering of CCAN

components CENP-C or CENP-I. Thus, almost 15 years after the original

suggestion by Warburton et al (1997), these beautiful experiments were

finally able to provide compelling evidence that CENP-A is sufficient for the

initiation of a feedback loop allowing for the stable inheritance of a

centromere structure.

The question that arises next is how CENP-A is able to specify a

centromere. One controversial hypothesis is that it is integrated into a

particle with a radically different conformation than canonical nucleosomes.

Indeed, a number of different conformational models have been proposed

(reviewed in Black & Cleveland, 2011), including heterotypic CENP-A/H3


27

nucleosomes (Lochmann & Ivanov, 2012), a stable (CENP-A/H4)2 tetramer

lacking H2A and H2B (Williams et al, 2009) and the replacement of H2A

and H2B by a non-histone protein (Mizuguchi et al, 2007). However, these

models are supported by a very limited amount and oftentimes ambiguous

evidence (Black & Cleveland, 2011). Nevertheless, the hemisome model,

where particles are composed of a single copy of CENP-A, H4, H2A, and

H2B, continually makes its way into high impact publications. The main

argument used in favor of the existence of hemisomes is that CENP-A

containing particles measured by atomic force microscopy (AFM) have a

reduced height of approximately 50% as compared to canonical

nucleosomes (Dalal et al, 2007; Dimitriadis et al, 2010; Bui et al, 2012).

However, a recent study suggested that AFM measurements of in vitro

reconstituted octameric CENP-A nucleosomes are in fact only half the size of

their H3 counterparts (Miell et al, 2013), perhaps due to a more flexible

packaging of DNA around the histone octamer (Palmer et al, 1987; Conde e

Silva et al, 2007; Tachiwana et al, 2011; Hasson et al, 2013). However, these

results have almost immediately been refuted by the Dalal and Henikoff

labs, practically the exclusive proponents of the hemisome model, after

measuring in vitro assembled octameric CENP-A nucleosomes at canonical

size ranges (Codomo et al, 2014; Walkiewicz et al, 2014), and it thus remains

unclear what the true height is of CENP-A nucleosomes (Miell et al, 2014).

Additional observations used in favor of the existence of hemisomes comes

from: 1) a nucleosome-crosslinking assay indicating the presence of a single

copy of each histone (Dalal et al, 2007), although this could easily be the

result of a missing crosslinkable lysine in CENP-ACID (Black & Bassett, 2008;

Zhang et al, 2012) as cysteine-crosslinking readily produced CENP-ACID

dimers (Zhang et al, 2012); 2) an apparent reversed directionality of DNA

supercoiling around the CENP-ACse4 particle, which would be most

consistent with a hemisomal conformation (Furuyama & Henikoff, 2009),

although alternative, energetically more favorable explanations for the

specific observations of the assay have been proposed (Black & Cleveland,

Chapter 1

28

2011); 3) questionable fluorescence microscopy analyses that are far from

conclusive (Bui et al, 2012; Shivaraju et al, 2012); 4) high resolution ChIP-

seq indicating that other DNA binding proteins surround an ~80 bp region

protected by CENP-ACse4 (Krassovsky et al, 2012), although the results are

equally consistent with nucleosomes protecting a ~120 bp region as would

be expected for CENP-A (see below); and 5) mapping of genome wide

histone H4 induced cleavage sites showing an atypical pattern on

centromeric sequences (Henikoff et al, 2014). As opposed to these equivocal

observations, there are many sources of compelling and highly reproducible

evidence arguing in favor of canonical octameric CENP-A nucleosomes: 1)

octamers are readily produced by in vitro reconstitution experiments (Yoda

et al, 2000; Camahort et al, 2009; Sekulic et al, 2010; Kingston et al, 2011;

Tachiwana et al, 2011), while hemisomes can only be produced under highly

artificial conditions (Furuyama et al, 2013); 2) CENP-A readily

homodimerizes in vitro through a dimerization domain analogous to that of

H3, mutation of which blocks in vitro dimerization and in vivo targeting of

CENP-A to centromeres (Palmer et al, 1991; Yoda et al, 2000; Black et al,

2004; Camahort et al, 2009; Bassett et al, 2012; Zhang et al, 2012); 3)

CENP-A particles protect ~120-150 bp of DNA from micrococcal nuclease

digestion, inconsistent with subnucleosomal sized particles (Palmer et al,

1987; Conde e Silva et al, 2007; Kingston et al, 2011; Zhang et al, 2012;

Hasson et al, 2013); 4) when purified from cells, particles consistently

contain two copies of CENP-A and stoichiometric levels of H4, H2A, and

H2B, and display similar biochemical properties as canonical nucleosomes

(Palmer et al, 1987; Shelby et al, 1997; Yoda et al, 2000; Foltz et al, 2006;

Camahort et al, 2009; Zhang et al, 2012; Padeganeh et al, 2013; Lacoste et

al, 2014); 5) co-immunoprecipitation of differentially tagged CENP-A shows

that mononucleosomal particles contain both species of this protein (Shelby

et al, 1997; Camahort et al, 2009; Zhang et al, 2012); and, most

compellingly, 6) X-ray crystal structures of CENP-A nucleosomes

(Tachiwana et al, 2011) and subnucleosomal CENP-A/H4-containing


29

particles (Sekulic et al, 2010; Cho & Harrison, 2011) show canonical

nucleosome conformations (albeit with subtle differences). Thus, although

there is still no absolute consensus in the field, the sum of existing evidence

strongly disfavors that centromeres are specified by CENP-A through an

alternative nucleosome arrangement. So it goes.

Assuming that CENP-A is part of a canonical nucleosome structure,

another differentiating principle from H3 nucleosomes is required. A

reasonable hypothesis is that there is an intrinsic feature of the CENP-A

histone itself that defines its unique properties. While the HFD of CENP-A

shares over 60% sequence identity (and ~75% similarity) with histone H3, a

very low level of homology exists between the N-terminal histone tails of

these two histones (Palmer et al, 1991; Sullivan et al, 1994). Surprisingly,

however, using chimeric proteins of H3 and CENP-A, it was shown that the

HFD rather than the tail of CENP-A is responsible for its centromere

targeting (Sullivan et al, 1994). Some 10 years later, Black et al (2004)

showed that the centromere targeting capacity lies within a region termed

CATD (for CENP-A targeting domain), consisting of loop1 and α2-helix of

the HFD (residues 75-114, containing 22 differences from H3.1).

Consistently, the CATD was shown to be responsible for recognition of

CENP-A by its specific histone chaperone and assembly factor HJUPR (Foltz

et al, 2009; Shuaib et al, 2010). In addition, the CATD was demonstrated to

confer reduced conformational rigidity to (CENP-A/H4)2 tetramers (Black et

al, 2004) as well as CENP-A nucleosomes (Black et al, 2007a), albeit by

distinct residues from those that are responsible for HJURP binding

(Bassett et al, 2012). Mutation of yet another portion of the CATD, a 2 amino

acid protruding bulge within loop 1, has been shown to reduce the stability

of CENP-A (Tachiwana et al, 2011). However, not the CATD, but a C-

terminal LEEGLG motif of CENP-A, absent from H3, is responsible for the

recruitment of the majority of downstream centromere and kinetochore

proteins (Carroll et al, 2010; Guse et al, 2011; Fachinetti et al, 2013),

although contradictory evidence suggests that the CENP-N binding capacity

Chapter 1

30

is either conferred by the CATD (Carroll et al, 2009) or by LEEGLG (Guse et

al, 2011). Remarkably, it was recently shown that a clean genetic

replacement of CENP-A with H3CATD is insufficient to rescue human cells,

but requires the addition of either the LEEGLG motif, or, surprisingly, the

CENP-A tail to the chimera (Fachinetti et al, 2013). Together, these results

strongly argue that multiple motifs or regions within CENP-A are

cooperatively responsible for its different centromere defining properties

that discriminate it from H3.

A model system for epigenetic inheritance

As discussed in the first section of the introduction, epigenetic traits are

heritable features that are not solely driven by underlying nucleotide

sequences. In the case of centromeres, with the sole exception of S.

cerevisiae and some closely related species, specific DNA sequences are

neither necessary nor sufficient for centromere identity. Nevertheless, (neo-)

centromeric loci are stably inherited throughout many divisions and even

over multiple human generations. Thus, it is clear that centromeres are not

only epigenetically defined, by that they are an example of transgenerational

epigenetic inheritance.

In addition, I discussed the basic properties of inheritance systems at the

very beginning of this thesis: propagation, replication, and regulation of a

carrier of information. It is now evident that the defining feature of

centromeres is the presence of CENP-A nucleosomes (Mendiburo et al,

2011), as has been hypothesized for many years (Warburton et al, 1997).

Only few other examples exist where it is as clear what the heritable defining

mark is, although perhaps gene silencing through DNA methylation is

another. Centromeric CENP-A is stably and quantitatively propagated

through both mitotic and meiotic divisions (Jansen et al, 2007; Dunleavy et

al, 2012; Raychaudhuri et al, 2012), with the only detectable loss of existing

molecules occurring through dilution during DNA replication (Jansen et al,

2007; Dunleavy et al, 2011; Bodor et al, 2013). A CENP-A specific histone


31

chaperone, HJURP, is responsible for replenishing CENP-A in each cell

cycle (Dunleavy et al, 2009; Foltz et al, 2009; Shuaib et al, 2010; Barnhart et

al, 2011), and is recruited to centromeres through a group of mutually

interacting proteins called Mis18α, Mis18β, and M18BP1 (Fujita et al, 2007;

Maddox et al, 2007; Barnhart et al, 2011; Wang et al, 2014). Additional

roles, potentially for stabilizing CENP-A nucleosomes after their assembly,

have been proposed for proteins of the RSF chromatin remodeling complex

(Perpelescu et al, 2009) and a molecular GTPase switch, regulated by

MgcRacGAP, Ect2, and Cdc42 (Lagana et al, 2010). Furthermore, assembly

of nascent CENP-A at centromeres is strictly coupled to the exit of mitosis in

animal cells (Jansen et al, 2007; Schuh et al, 2007; Hemmerich et al, 2008;

Bernad et al, 2011; Silva et al, 2012), and regulated through the core

machinery driving the cell cycle (Silva et al, 2012; McKinley & Cheeseman,

2014; Müller et al, 2014; Wang et al, 2014). Thus, all the basic properties of

an inheritance system discussed in the beginning of this introduction

(propagation, replication, regulation) evidently apply to CENP-A,

underlining its role in centromere inheritance.

Intriguingly, there is some indirect evidence that centromeres can play a

role in (karyotype) evolution. Unlike most well-studied epigenetic traits,

(neo-) centromeric loci can be transgenerationally inherited. In agreement

with this, it was shown that presence of parental CENP-ACID is essential in

Drosophila to initiate centromere functionality in embryos of the next

generation (Raychaudhuri et al, 2012). Moreover, it appears that

neocentromeres can rapidly become fixed in a population. Evolutionary new

centromeres, where centromere positions have an independent evolutionary

history from flanking chromosomal regions, have been reported for many

mammals (including primates), birds, and plants (Montefalcone et al, 1999;

Kasai et al, 2003; Nagaki et al, 2004; Ventura et al, 2004; Rocchi et al,

2012). Remarkably, five separate centromere repositioning events took place

between zebra (Equus burchelli) and donkey (Equus asinus), which diverged

from each other less than one million years ago, i.e. within a very short

Chapter 1

32

window of evolutionary time (Carbone et al, 2006). Moreover, multiple

donkey chromosomes exist where the typical centromeric satellite DNA is

present at a genomic locus that is distinct from the active centromere, which

is formed on complex DNA (Piras et al, 2010), arguing that centromere

repositioning was the result of neocentromere formation. Similarly, non-

repetitive centromeres have been found on specific chromosomes in

multiple other equine species (Carbone et al, 2006; Wade et al, 2009; Piras

et al, 2010), chicken (Shang et al, 2010), and orangutan (Locke et al, 2011).

In light of this, it has been argued that neocentromere formation and

centromere repositioning are one and the same phenomenon, observed at

different timescales (Capozzi et al, 2008). Moreover, it has been argued that

neocentromere formation may have the capacity to drive, or at least

potentiate, karyotype evolution through a non-Mendelian mechanism called

meiotic drive: biased chromosome segregation to polar bodies during female

meiosis (Henikoff et al, 2001; Amor et al, 2004). Indeed, a bias in the

retention rate of Robertsonian (telomere-to-telomere) fusion chromosomes

has been observed in humans (Pardo-Manuel de Villena & Sapienza, 2001a)

and multiple other mammalian species (Pardo-Manuel de Villena &

Sapienza, 2001b). Recently, in a groundbreaking study, it was demonstrated

that meiotic drive in mice can act through differential centromere ‘strength,’

as measured by the density of the microtubule binding Ndc80-complex

member HEC1 (Chmátal et al, 2014). Moreover, the authors were able to

show that in several wild mouse populations, a reduced karyotype (from 2n

= 40 to 2n = 22–28) was correlated with stronger centromeres on

metacentric (internal centromere) Robertsonian fusion chromosomes than

on chromosomes with a typical telocentric (centromere next to telomere)

arrangement (Chmátal et al, 2014). Thus, a similar mechanism may act on

neocentromeres, where an altered strength would lead to their preferential

maintenance and, ultimately, fixation in a population. Taken together,

irrespective of their hypothetical role in evolution, the evidence listed above

likely makes centromeres the most stable epigenetic trait known to date.


33

Furthermore, there are practical reasons that facilitate the study of

centromeres. Importantly, they are essential cellular structures for which

there are clear and easily measurable functional readouts of failure: mitotic

defects. Furthermore, microscopy analysis and quantification are greatly

facilitated by their distinct localization pattern as subnuclear, resolution

limited foci (Bodor et al, 2012). Finally, as a result of over 120 years of

centromere research and almost three decades of studying CENP-A, a

wealth of knowledge as well as molecular tools have become readily

available to the scientific community. In summary, inherent as well as

practical aspects of centromeres and CENP-A make them an excellent model

system for the study of epigenetic inheritance.

However, as Johan Cruijff famously said: “elk voordeel hep se nadeel”

(“every advantage ‘as ‘is disadvantage”). Indeed, the study of centromeres

does not come without its frustrations. Notably, the highly repetitive nature

of centromeres put them among the last regions in the genomes of most

species for which the sequence remains elusive (Alkan et al, 2011). This

forms a great obstacle for certain types of analysis of centromeres, such as

chromatin immunoprecipitation (ChIP) experiments or determining the

elusive role of centromeric transcription. However, promising advances in

sequencing technologies and data-analysis are starting to allow for the

characterization of highly repetitive genomic regions, including centromeres

(Alkan et al, 2011; Hayden, 2012; Hayden & Willard, 2012; Hayden et al,

2013; Altemose et al, 2014; Miga et al, 2014). Another difficulty is that

centromeres are remarkably resistant to depletion of CENP-A (Liu et al,

2006; Black et al, 2007b; Fachinetti et al, 2013), which is likely due to the

extreme stability of CENP-A nucleosomes (Jansen et al, 2007; Bodor et al,

2013). Nevertheless, despite these shortcomings, over the last few decades

centromere biology has become an exciting and dynamic field of study.

Chapter 1

34

QUANTITATIVE BIOLOGY

Biology is not an exact science. Unlike e.g. physical and chemical

processes, biological mechanisms cannot be fully captured in mathematical

formulas. Similarly, measurements in biological systems suffer from a fairly

large degree of biological variation. Although it is arguable that, once all of

the underlying physical and chemical processes are fully understood, it is in

principle possible to precisely measure biological system and express them

in mathematical terms, this is practically impossible. Despite this, a wealth

of knowledge can be acquired from quantification in biological research, and

oftentimes surprising findings are made (e.g. Meyer-Rochow & Gal, 2003).

Why quantify biology anyway?

In order to gain a proper understanding of a (biological) process, it is

important to consider a number of features of the system. First, it is

necessary to know the key players participating in the system. For this

reason, much of biological research has been focused on finding genes and

proteins that are involved in a particular process, oftentimes by performing

forward or reverse genetic or proteomic screens. Next, it is important to

know what each component does and how they interact with and depend on

each other. A large number of techniques are used in biology to determine

this, e.g. biochemical assays, in vitro reconstitutions, genetic hierarchy

analysis, etc., etc. Finally, it is essential to quantify the (relative) amount of

each of the components. However, in biological research, this parameter is

often overlooked. Accordingly, relatively few techniques exist that allow for

the accurate measurement of molecular copy numbers. Nevertheless, all of

the aspects raised above are essential to fully understand what is going on.

If taken to an extreme, it becomes obvious that the number of molecules

is an essential parameter in the regulation of a process. In a hypothetical

scenario, a given function can either be performed by a single molecule or

collectively by a very large number of (identical) molecules. While even a

small perturbation has a dramatic effect on a process that is dependent on a


35

single molecule (e.g. if this molecule is lost or damaged), only major

deviations will affect a system driven by a large population of molecules.

Similarly, for structures that can exist in multiple different states (e.g. active

or inactive), a system consisting of a single entity will always either be fully

active or fully inactive. Conversely, the law of large numbers dictates that the

higher the number of units, the closer the system will be to equilibrium at

any moment (Bernoulli, 1713). Although these examples take an extreme

standpoint, they do have at least some biological relevance. Indeed, there is

evidence in the pathogenic yeast C. albicans that the dam1 complex, which

plays a role in stabilizing kinetochore-microtubule interactions and is

essential in this species, becomes redundant if the single endogenous

kinetochore-microtubule is experimentally increased to more than one

(Burrack et al, 2011). Thus, information about the statistical and stochastic

properties of a process is obtained by determining where the number of

components lies on the scale of one to infinity.

Even when far removed from extreme values, knowledge of the number

of molecules provides information about the physical properties of a system.

Naturally, four oxen can pull a heavier load than two. Similarly, biological

entities will be able to, e.g., exert or resist more force, adhere more strongly,

or react to a stimulus faster, depending on the number of physical modules.

A clear example is that of dynein, a molecular motor that is able to utilize

energy obtained from ATP hydrolysis to transport cargo along the surface of

a microtubule (Goldstein & Yang, 2000). The amount of force that each

dynein molecule can generate has been carefully measured to be in the pN

range (Kamimura & Takahashi, 1981; Ashkin et al, 1990). Given the high

cytoplasmic viscosity as well as the large volume and mass of certain pieces

of cargo, this amount of force may not suffice and in many cases multiple

dynein motors act simultaneously on the same piece of cargo (Ashkin et al,

1990). Therefore, the amount of force that each motor can exert, the amount

of force required to drag cargo, as well as the number of motors present are

all essential factors to understand the mechanics of subcellular transport.

Chapter 1

36

How to measure absolute copy numbers in biological systems?

The total amount of a given protein per cell can be measured using a

number of different techniques. A fairly straightforward strategy is the

quantitative comparison of purified (recombinant) protein of a known

concentration with lytic extracts of a known number of cells, e.g. by Western

blot (Higgs et al, 1999) or mass spectrometry (Gerber et al, 2003; Beynon et

al, 2005). Recent advances in fluorescent immunoblotting have aided

accurate quantification by increasing the linear range of detection (Schutz-

Geschwender et al, 2004; Wang et al, 2007). An alternative strategy is to

immobilize fluorescently tagged proteins from extracts on functionalized

glass surfaces after which single molecule imaging can be used to determine

the number of molecules (Jiang et al, 2010). While these methods allow for

the determination of the average number of molecules in a population of

cells, information of the variance, and thus of the actual number of

molecules in any cell, is lost. Thus, to avoid averaging over a large

population, single cell techniques have been developed, e.g. by using

microfluidic chambers (Huang et al, 2007). However, these whole cell

quantification methods usually don’t give information about the number of

molecules that actually take part in any single structure or event.

Figure 1.3 (next page) Methods that allow for the determination molecular copy numbers. (A) Fluorescence

correlation spectroscopy measures the autocorrelation of fluorescence intensity over time within a minute volume. Stars

represent fluorophores; arrows represent movement over (discrete) time steps; red stars and line segments represent

fluorescently active molecules. (Sample data and conversion function were adapted from: Weidemann & Schwille, 2009)

(B) Stepwise photobleaching is used to measure discreet steps in fluorescence decay until background intensity is

reached (image adapted from: Leake et al, 2006). (C) Superresolution microscopy can be used to count individual

fluorescence activation events (image adapted from: Gunzenhäuser et al, 2012). (D) Fluorescent standards are used as a

reference of comparison to signal intensities of a structure of interest. In this case, Cse4-GFP intensity is compared to 4

different molecular standards. Images of purified GFP molecules are averaged over 8 frames and acquired at 2.5 fold

higher exposure times. Graph shows the average fluorescence intensity per GFP molecule (in grey) for the different

standards as well as Cse4-GFP count (in red) based on these particular standards (image adapted from: Lawrimore et al,

2011). *: note that the maximum possible number of LacI-GFP molecules on a 4 kb Lac array is indicated and used as

fluorescent standard. (E) Internally calibrated ratiometry determines the relative fluorescence of a structure of interest

compared to the fluorescence of the entire cell. In combination with measurements of the total amount of proteins

present in the cell (in this case by comparative western blot against purified protein, right panel), this allows for copy

number measurements that are independent of external references (image adapted from: Bodor et al, 2014).


37

Chapter 1

38

A number of additional difficulties arise when molecule copy numbers

are interrogated at subcellular locations. Analysis usually relies on imaging-

based methods, for which cells must retain a certain level of integrity –

ideally live cells are used— rather than using protein extracts. In addition,

every single copy of the molecule of interest must be accounted for, which

ideally requires the genetic replacement of an endogenous protein with a

(fluorescently) tagged version. Alternatively, in specific cases electron

microscopy can be used (e.g. Ashkin et al, 1990), although complex and

intrusive preparation techniques are required, which may likely affect the

number of molecules detected. Below, a number of strategies to determine

local molecular copy numbers using fluorescence microscopy are discussed.

Fluorescence correlation spectroscopy (FCS) is a well-known method to

determine local protein concentrations (Figure 1.3A). This technique

measures the fluctuation of fluorescence from molecules that pass through a

sub-femtoliter volume, i.e. ~5 orders of magnitude smaller than a eukaryotic

cell (Schwille, 2001). In effect, this allows for the determination of fluoro-

phore copy numbers within the excitation volume (Koppel et al, 1976), and

can be repeated in different cellular regions to determine the distribution

throughout the cell (Heinrich et al, 2013). One shortcoming of FCS is that is

relies on Brownian motion of fluorophores and therefore is not applicable if

the proteins are relatively immobile and/or stably bound to large structures.

Stepwise photobleaching is a method that relies on the stochastic ir-

reversible bleaching of individual fluorophores due to light exposure (Leake

et al, 2006). By continuously exciting samples at a low intensity, fluoro-

phores will bleach at a low frequency such that it is possible to determine the

number of events that occurred before background levels are reached

(Figure 1.3B). However, it becomes progressively more difficult to separate

individual bleaching events with increasing number of fluorophores (Ulbrich

& Isacoff, 2007). Thus, it has been estimated that the maximum number of

molecules that can be accurately counted by stepwise photobleaching, even

after mathematical extrapolations, lies around 30 (Coffman & Wu, 2012).


39

More recently, the principle of super-resolution microscopy has been

applied to determine molecule copy numbers (Gunzenhäuser et al, 2012;

Lando et al, 2012). In this case, somewhat opposite to stepwise

photobleaching, activation events of photoconvertible fluorescent proteins

are counted (Figure 1.3C). Individual fluorophores are successively

activated, counted, and bleached prior to activation of a subsequent

fluorophore at the same site. Gunzenhauser et al (2012) were able to

convincingly show that, by combining usage of optimal photo-convertible

fluorescent proteins with specific buffer and imaging conditions and

sophisticated analysis techniques, accurate counts of up to ~1000 molecules

can be produced. However, due to the complex nature of the experimental

techniques, microscope setups, and image analysis, it will likely take some

time before this strategy will become common practice in the scientific

community.

The use of fluorescent standards is a fairly straightforward way to

measure fluorophore copy numbers. Structures containing a known number

of fluorophores, either determined by independent methods or synthesized

to contain a calibrated number of molecules, called fluorescent standards,

are imaged alongside with a fluorescent structure of interest. If imaged

under identical conditions, their relative fluorescence is a direct readout of

the ratio of fluorescent molecules between the two structures (Coffman &

Wu, 2012). However, the fluorescence properties of most fluorophores are

affected by their local environment (Suhling et al, 2002), most notably by

the pH (Campbell & Choy, 2001; Griesbeck et al, 2001; Suhling et al, 2002).

Similarly, maturation dynamics of fluorescent proteins (i.e. the time

between protein production and emergence of their fluorescent potential)

have been shown to depend on external conditions, such as temperature

(Macdonald et al, 2012) or growth media supplements (Hebisch et al, 2013).

Because both the environment and its effect on the fluorophore are hard to

determine in vivo, a potential effect on ratiometric measurements of

fluorescence intensities cannot be excluded. Nevertheless, recently, four

Chapter 1

40

highly diverse fluorescent standards (purified EGFP; virus like particles;

bacterial flagellar motor proteins; and a calibrated LacO/LacI-system) were

used to measure the number of centromeric CENP-ACse4 molecules in

budding yeast (Figure 1.3D), all of which essentially producing the same

result (Lawrimore et al, 2011). This indicates that environmental factors may

not significantly affect these measurements, at least for the particular

fluorescent protein (EGFP) used.

Internally calibrated fluorescence comparisons (Figure 1.3E) provide

perhaps the most elegant method to determine local protein abundance. In

this case, fluorescence measurements are made both of the total cellular

volume and of the specific region of interest. Combining the ratio of

fluorescence between these two with a measurement of the total protein

concentration (e.g. by western blot as described above), gives a direct

readout of local protein copy numbers (Wu & Pollard, 2005; Wu et al,

2008). Although performing all required corrections and determining

complex cell shapes is not trivial, the main advantage of this method is that

it is fully internally controlled.

It goes without saying that this inventory of potential methods to

quantify molecular copy numbers is far from complete. Nevertheless, for

most techniques, there are relatively few examples in the literature where

they have been used, likely due to their complex nature. Importantly, given

that each method has its own pitfalls and shortcomings, ideally a

combination of strategies should be used to gain confidence in the

measurements.

How many CENP-A molecules are there in a centromere?

One specific case for which it is important to know the number of

molecules present is centromeric CENP-A. Because CENP-A chromatin

constitutes an epigenetic mark, an essential molecular unit of information

that cannot be lost, the fidelity of centromere propagation is ultimately

dependent on the number of nucleosomes present. For this (and other)


41

reasons, many attempts have been made to measure the centromeric

abundance of CENP-A in a variety of species. Consistent with the difficulty

of performing copy number measurements, as described above,

discrepancies between measurements performed in different studies exist in

many cases. Below, I will give an overview of all the different measurements

performed to my knowledge to date (see also Table 1.1) and discuss potential

reasons for disagreement.

Budding yeast was the first species where careful analysis of the number

of CENP-ACse4 nucleosomes per centromere was performed. Given that

centromeric DNA is non-repetitive in this species, ChIP experiments showed

a strong enrichment of CENP-ACse4 for the ~125 base pair centromere core,

although some binding of neighboring sequences was also detected (Meluh

et al, 1998). A very elegant follow-up experiment by Furuyama and Biggins

(2007) showed that ChIPped fragments of mononucleosomal size contain

centromeric DNA, but not the surrounding sequences, strongly suggesting

that budding yeast centromeres harbor a single CENP-ACse4 nucleosome.

Given this apparently clean biochemical evidence, centromeric foci of this

species (containing 16 clustered centromeres and 2 CENP-ACse4 molecules

per nucleosome) have been extensively used as a molecular standard for 32

fluorescent molecules (Joglekar et al, 2006, 2008; Johnston et al, 2010;

Schittenhelm et al, 2010). However, this may not have been the most

reliable choice, as the one-nucleosome hypothesis has been challenged

recently by two microscopy-based studies that used external fluorescent

standards to determine that budding yeast centromeres contain on average

3.5–8 CENP-ACse4 molecules (Coffman et al, 2011; Lawrimore et al, 2011).

Furthermore, it was shown that the amount of CENP-ACse4 can be reduced

by ~40–60%, without affecting kinetochore-microtubule attachments

(Haase et al, 2013), inconsistent with a single nucleosome per centromere.

Mathematical simulations argue that due to the relatively high detection

limit, CENP-ACse4 outside of centromeres would not be observed in the ChIP

experiments of Furuyama & Biggins (2007) if their nucleosome positions are

Chapter 1

42

sufficiently variable (Lawrimore et al, 2011). Nevertheless, yet other recent

analyses maintain that budding yeast centromeres contain a single

nucleosome, based on high sensitivity ChIP-Seq experiments (Henikoff &

Henikoff, 2012), FCS measurements (Shivaraju et al, 2012), stepwise

photobleaching of the kinetochore protein Spc24 at a single centromere

(Aravamudhan et al, 2013), or fluorescence comparison to TetR on an

intergrated TetO array of carefully determined size (Wisniewski et al, 2014).

Potential explanations for the discrepancy between the different studies can

be sought in the use of different strains (as argued by Lawrimore et al, 2011);

potential pre-nucleosomal or unincorporated CENP-ACse4 at centromeres (as

argued by Henikoff & Henikoff, 2012), potential artifacts induced by

fluorescent tags (as argued by Henikoff & Henikoff, 2012 and Wisniewski et

al, 2014), and/or complex dynamics of photochemical maturation times of

fluorescent proteins at the budding yeast centromere (Wisniewski et al,

2014), perhaps in combination with measurement inaccuracy of often very

dim signals. Nevertheless, although the verdict is still out on the precise

number of CENP-ACse4 molecules per centromere, a general agreement exists

that few (≤4) nucleosomes are present (Table 1.1).

The amount of CENP-A per centromere was analyzed in two other yeast

species. CENP-ACse4 was used as a fluorescent standard to measure the

amount of CENP-A at C. albicans and fission yeast centromeres. After

correction for the number of centromeres per cluster in each species,

CENP-ACaCse4 was found to be ~4 times as abundant at C. albicans

centromeres as CENP-ACse4 in budding yeast (Joglekar et al, 2008).

Therefore, depending on the true number in budding yeast, C. albicans has

between 8 and 32 molecules of CENP-ACaCse4 (4–16 nucleosomes) per

centromere. For fission yeast, the authors found that CENP-ACnp1 is ~2.5

times as abundant at the centromeres of this species as in budding yeast

(Joglekar et al, 2008), arguing that there are on average 5–20 molecules per

centromere (2.5–10 nucleosomes). However, it was recently found that the

fission yeast strain used for these comparisons likely expressed competing


43

wildtype CENP-ACnp1 in addition to the measured CENP-ACnp1-GFP (Coffman

et al, 2011), which would confound the measurements. To reevaluate the

measured numbers, stepwise photobleaching was performed to calibrate a

different fluorescent standard, the bacterial flagellar motor protein MotB

(Leake et al, 2006; Coffman et al, 2011), and was used to show that 226

molecules of CENP-ACnp1 are present per centromere in a clean genetic

substitution strain of fission yeast (Coffman et al, 2011). More recently, a

super-resolution-based method was employed to count the amount of

CENP-ACnp1 at centromeres and found ~20 molecules per centromere

(Lando et al, 2012). In addition, using high-resolution ChIP-Seq, the same

study showed that, in total, the central domains of all three fission yeast

centromeres only displayed 64 discrete peaks of CENP-ACnp1 (Lando et al,

2012). The authors used this result to argue that no more than 128

molecules of CENP-ACnp1 can be present at centromere foci (~43 per

centromere), although it must be noted that a substantial number of peaks

in the outer repeats of fission yeast centromeres were ignored. At present,

given the rather large discrepancies observed between studies, it is difficult

to make a final conclusion as to what the correct number of CENP-ACnp1

molecules per fission yeast centromere is (Table 1.1).

Only few efforts have been reported to measure the amount of CENP-A

at metazoan centromeres. One study used, yet again, CENP-ACse4 as a

fluorescent standard to measure CENP-ACID levels in Drosophila wing

imaginal discs (Schittenhelm et al, 2010). According to their measurements,

84–336 molecules of CENP-ACID are present per centromere, depending on

how many there are in budding yeast. It must be noted however, that there

are multiple experimental issues that may confound the results in this study.

Importantly, rather than quantifying centromere specific signals,

measurements were made on regions that are larger than an entire nucleus

and thus including fluorescence derived from non-centromeric CENP-A, the

levels of which can be surprisingly high and even exceed the centromeric

levels (Bodor et al, 2014; Lacoste et al, 2014). In addition, it remains

Chapter 1

44

unexplained why a large variation in the extent of fluorescence reduction at

increasing focal depth is observed for different proteins. In C. elegans, a

holocentric organisms (Albertson & Thomson, 1982), ChIP experiments

show that CENP-AHCP-3 can be found on ~40–60% of the genome

(Gassmann et al, 2012). However, the total chromatin-bound pool is only

sufficient to represent 3–4% of all nucleosomes (Gassmann et al, 2012),

arguing that the precise location of CENP-A is highly variable between

individuals. Two studies have reported numbers on the amount of CENP-A

in chicken DT40 cells, although both caution that the presence of untagged

CENP-A likely confounds their copy number measurements. Johnston et al

(2010) rounded up the usual suspect, CENP-ACse4, as a fluorescent standard

and report that there are at least 62 molecules of CENP-A per centromere

(based on a single CENP-ACse4 nucleosome). Ribeiro et al (2010) count

photoblinking events of a photoconvertible fluorescent protein to estimate

that there are between 25 and 40 molecules of CENP-A-Dronpa present (in

addition to the unlabeled CENP-A), although they admit that their

measurements are further hampered by the fact that the photoblinking

properties of this probe are quite variable (Habuchi et al, 2005; Flors et al,

2007). Prior to my own work, no careful quantification has been made for

human CENP-A on a per centromere basis. In fact, to my knowledge, the

only reported estimation comes from a study where the total cellular pool of

CENP-A, measured at 2×106 molecules per HeLa cell, was divided over the

average number of chromosomes present in this cell line and states that the

maximum amount of CENP-A per centromere is ~30.000 (Black et al,

2007b). As discussed extensively in Chapter 4, I have now carefully

measured the centromeric CENP-A copy number in human RPE cells to be

on average 400, although minor differences exist between specific cell lines

(Bodor et al, 2014; and see Table 1.1).


45

Table 1.1 Overview of published number of CENP-A molecules per centromere for different species

Spec

ies

Spci

es s

pec

ific

nam

e o

f C

ENP

-AR

efe

ren

ce

mo

lecu

les/

CEN

(nu

cleo

som

es/

CEN

)aM

eth

od

No

tes

bu

dd

ing

yeas

t

(S. c

erev

isia

e)

Cse

4Fu

ruya

ma

& B

iggi

ns

(20

07

)(1

)C

hIP

-PC

R-

CEN

DN

A, b

ut

no

t su

rro

un

din

g se

qu

ence

s, o

f m

on

on

ucl

eoso

mal

siz

e w

ere

det

ecte

d a

fte

r C

ENP

-A C

hIP

Co

ffm

an e

t al

(2

01

1)

8Fl

uo

resc

en

t st

and

ard

(bac

teri

al M

otB

)-

Mo

tB c

op

y n

um

ber

was

cal

ibra

ted

by

ste

pw

ise

ph

oto

ble

ach

ing

Law

rim

ore

et

al (

20

11

)3

.5 –

6Fl

uo

resc

en

t st

and

ard

s

(mu

ltip

le)

- D

iffe

ren

t am

ou

nts

we

re o

bse

rved

dep

end

ing

on

th

e sp

ecif

ic s

trai

n u

sed

- Fl

uo

resc

en

t st

and

ard

s: m

GFP

, Vir

us

like

par

ticl

es, M

otB

, Lac

I

Hen

iko

ff &

Hen

iko

ff (

20

12

)(1

)C

hIP

-Seq

- D

ata

is p

rese

nte

d in

a w

ay t

hat

is h

ard

to

eva

luat

e th

eir

argu

men

tati

on

Shiv

araj

u e

t al

(2

01

2)

1 –

2

(1)

FCS

+ f

luo

resc

en

t st

and

ard

(Nu

p4

9)

- Th

e au

tho

rs a

rgu

e th

at t

her

e is

a s

ingl

e n

ucl

eoso

me,

bu

t th

at it

cyc

les

bet

we

en a

hem

iso

mal

an

d c

ano

nic

al c

on

form

atio

n

- C

han

ges

in c

entr

om

ere

mo

rph

olo

gy t

hro

ugh

ou

t m

ito

sis

wo

uld

aff

ect

FCS

mea

sure

men

ts, b

ut

we

re n

ot

take

n in

to a

cco

un

t

- N

up

49

is a

su

bo

pti

mal

sta

nd

ard

, as

the

sign

al is

hig

hly

dis

per

sed

an

d

het

ero

gen

eou

s

Haa

se e

t al

(2

01

3)

≥ 4

Red

uct

ion

of

CEN

P-A

in

mu

tan

ts

- D

esp

ite

a 4

0-6

0%

red

uct

ion

in Δ

Pat

1 a

nd

ΔX

rn1

, all

cen

tro

mer

es w

ere

able

to

mak

e st

able

mic

rotu

bu

le c

on

nec

tio

ns

Ara

vam

ud

han

et

al (

20

13

)1

.7 –

2B

iFC

+ s

tep

wis

e

ph

oto

ble

ach

ing

of

Spc2

5

- B

iFC

arg

ues

a m

inim

um

of

2 m

ole

cule

s p

er C

EN. S

pc2

4:C

ENP

-A r

atio

was

det

erm

ined

in J

ogl

ekar

et

al (

20

06

)

Wis

nie

wsk

i et

al (

20

14

)2

.25

Flu

ore

sce

nt

stan

dar

d (

TetR

)-

TetO

-arr

ays

of

dif

fere

nt

size

s w

ere

use

d

C. a

lbic

an

sC

se4

/ C

aCse

4Jo

glek

ar e

t al

(2

00

8)

8 –

32

Flu

ore

sce

nt

stan

dar

d

(bu

dd

ing

yeas

t C

se4

)-

Co

rrec

t n

um

ber

dep

end

s o

n t

he

amo

un

t p

rese

nt

in b

ud

din

g ye

ast

fiss

ion

yea

st

(S. p

om

be)

Cn

p1

Jogl

ekar

et

al (

20

08

)5

– 2

0Fl

uo

resc

en

t st

and

ard

(bu

dd

ing

yeas

t C

se4

)

- C

orr

ect

nu

mb

er d

epen

ds

on

th

e am

ou

nt

pre

sen

t in

bu

dd

ing

yeas

t

- M

easu

rem

ents

may

be

con

fou

nd

ed b

y n

on

-flu

ore

sce

nt

CEN

P-A

th

at is

po

ten

tial

ly

exp

ress

ed in

ad

dit

ion

to

GFP

tag

ged

pro

tein

Co

ffm

an e

t al

(2

01

1)

22

7Fl

uo

resc

en

t st

and

ard

(bac

teri

al M

otB

)-

Mo

tB c

op

y n

um

ber

was

cal

ibra

ted

by

ste

pw

ise

ph

oto

ble

ach

ing

Lan

do

et

al (

20

12

)~2

0 /

≤ 4

3P

ALM

/ C

hIP

-Seq

- A

su

bst

anti

al n

um

ber

of

Ch

IP-S

eq p

eaks

in o

ute

r re

pea

ts w

ere

ign

ore

d

Yao

et

al (

20

13

)2

6 –

10

4Fl

uo

resc

en

t st

and

ard

(bu

dd

ing

yeas

t N

dc8

0)

- D

ata

was

no

t sh

ow

n a

nd

th

e ex

per

imen

t w

as n

ot

des

crib

ed in

th

e ex

per

imen

tal

pro

ced

ure

s

- C

orr

ect

nu

mb

er d

epen

ds

on

th

e am

ou

nt

pre

sen

t in

bu

dd

ing

yeas

t

D. m

ela

no

ga

ster

(win

g im

agin

al d

isc)

CID

Sch

itte

nh

elm

et

al (

20

10

)8

4 –

33

6Fl

uo

resc

en

t st

and

ard

(bu

dd

ing

yeas

t C

se4

)

- C

orr

ect

nu

mb

er d

epen

ds

on

th

e am

ou

nt

pre

sen

t in

bu

dd

ing

yeas

t

- M

easu

rem

ent

of

tota

l ch

rom

atin

bo

un

d C

ENP

-A r

ath

er t

han

cen

tro

mer

e sp

ecif

ic

po

ol

- U

nco

nve

nti

on

al c

orr

ecti

on

s w

ere

per

form

ed

chic

ken

(D

T40

)C

ENP

-A /

ggC

ENP

-AR

ibei

ro e

t al

(2

01

0)

25

– 4

0P

ho

tob

linki

ng

eve

nts

- P

rese

nce

of

un

tagg

ed C

ENP

-A is

no

t ac

cou

nte

d f

or

- N

um

ber

of

ph

oto

blin

kin

g e

ven

ts p

er m

ole

cule

are

err

atic

Joh

nst

on

et

al (

20

10

)≥

62

– 2

48

Flu

ore

sce

nt

stan

dar

d

(bu

dd

ing

yeas

t C

se4

)

- P

rese

nce

of

un

tagg

ed C

ENP

-A is

no

t ac

cou

nte

d f

or

- C

orr

ect

nu

mb

er d

epen

ds

on

th

e am

ou

nt

pre

sen

t in

bu

dd

ing

yeas

t

hu

man

(H

eLa)

Bla

ck e

t al

(2

00

7b

)≤

30

.00

0W

ho

le c

ell i

mm

un

ob

lott

ing

- M

axim

um

est

imat

ion

if a

ll ce

llula

r C

ENP

-A w

ou

ld b

e ce

ntr

om

ere

loca

lized

hu

man

(R

PE)

Bo

do

r et

al (

20

14

)~

40

03

ind

epen

den

t m

eth

od

s-

Des

crib

ed in

ch

apte

r 4

hu

man

(mu

ltip

le c

ell l

ines

)B

od

or

et a

l (2

01

4)

10

0 –

57

9Fl

uo

resc

en

t st

and

ard

(R

PE

CEN

P-A

)

- C

ell l

ines

mea

sure

d (

mo

lecu

les/

CEN

): D

LD-1

(1

00

); H

CT-

11

6 (

17

7);

HeL

a (2

63

); G

M0

61

70

pri

mar

y fi

bro

bla

sts

(33

6);

U2

OS

(57

0);

PD

NC

-4 (

57

9)

a : Th

e n

um

ber

s sh

ow

n in

th

is t

able

co

rres

po

nd

s to

eit

her

mo

lecu

les

per

cen

tro

mer

e o

r n

ucl

eoso

mes

per

cen

tro

mer

e, c

orr

esp

on

din

g to

wh

at w

as d

escr

ibed

in t

he

rele

van

t re

fere

nce

Chapter 1

46

REFERENCES

Agrawal AA, Laforsch C & Tollrian R (1999) Transgenerational induction of defences in animals and plants. Nature 401: 60–63

Ahmad K & Henikoff S (2002) The histone variant H3.3 marks active chromatin by replication-independent nucleosome assembly. Mol. Cell 9: 1191–1200

Akiyoshi B & Gull K (2013) Evolutionary cell biology of chromosome segregation: insights from trypanosomes. Open Biol. 3: 130023

Alabert C & Groth A (2012) Chromatin replication and epigenome maintenance. Nat. Rev. Mol. Cell Biol. 13: 153–167

Albertson DG & Thomson JN (1982) The kinetochores of Caenorhabditis elegans. Chromosoma 86: 409–428

Alkan C, Cardone MF, Catacchio CR, Antonacci F, O’Brien SJ, Ryder OA, Purgato S, Zoli M, Valle GD, Eichler EE & Ventura M (2011) Genome-wide characterization of centromeric satellites from multiple mammalian genomes. Genome Res. 21: 137–145

Altemose N, Miga KH, Maggioni M & Willard HF (2014) Genomic characterization of large heterochromatic gaps in the human genome assembly. PLoS Comput. Biol. 10: e1003628

Amon A, Irniger S & Nasmyth K (1994) Closing the cell cycle circle in yeast: G2 cyclin proteolysis initiated at mitosis persists until the activation of G1 cyclins in the next cycle. Cell 77: 1037–1050

Amor DJ, Bentley K, Ryan J, Perry J, Wong L, Slater H & Choo KHA (2004) Human centromere repositioning ‘in progress’. Proc. Natl. Acad. Sci. U. S. A. 101: 6542–6547

Aragon L, Martinez-Perez E & Merkenschlager M (2013) Condensin, cohesin and the control of chromatin states. Curr. Opin. Genet. Dev. 23: 204–211

Aravamudhan P, Felzer-Kim I & Joglekar AP (2013) The Budding Yeast Point Centromere Associates with Two Cse4 Molecules during Mitosis. Curr. Biol. 23: 770–774

Ashkin A, Schütze K, Dziedzic JM, Euteneuer U & Schliwa M (1990) Force generation of organelle transport measured in vivo by an infrared laser trap. Nature 348: 346–348

Avery OT, MacLeod CM & McCarty M (1944) Studies on the Chemical Nature of the Substance Inducing Transformation of Pneumococcal Types Induction of Transformation by a Desoxyribonucleic Acid Fraction Isolated from Pneumococcus Type III. J. Exp. Med. 79: 137–158

Bannister AJ & Kouzarides T (2011) Regulation of chromatin by histone modifications. Cell Res. 21: 381–395

Barnhart MC, Kuich PHJL, Stellfox ME, Ward JA, Bassett EA, Black BE & Foltz DR (2011) HJURP is a CENP-A chromatin assembly factor sufficient to form a functional de novo kinetochore. J. Cell Biol. 194: 229–243


47

Barski A, Cuddapah S, Cui K, Roh T-Y, Schones DE, Wang Z, Wei G, Chepelev I & Zhao K (2007) High-resolution profiling of histone methylations in the human genome. Cell 129: 823–837

Bassett EA, DeNizio J, Barnhart-Dailey MC, Panchenko T, Sekulic N, Rogers DJ, Foltz DR & Black BE (2012) HJURP uses distinct CENP-A surfaces to recognize and to stabilize CENP-A/histone H4 for centromere assembly. Dev. Cell 22: 749–762

Benson LJ, Gu Y, Yakovleva T, Tong K, Barrows C, Strack CL, Cook RG, Mizzen CA & Annunziato AT (2006) Modifications of H3 and H4 during chromatin replication, nucleosome assembly, and histone exchange. J. Biol. Chem. 281: 9287–9296

Berger SL, Kouzarides T, Shiekhattar R & Shilatifard A (2009) An operational definition of epigenetics. Genes Dev. 23: 781–783

Bernad R, Sánchez P, Rivera T, Rodríguez-Corsino M, Boyarchuk E, Vassias I, Ray-Gallet D, Arnaoutov A, Dasso M, Almouzni G & Losada A (2011) Xenopus HJURP and condensin II are required for CENP-A assembly. J. Cell Biol. 192: 569–582

Bernoulli J (1713) Ars conjectandi. Basileae, Switzerland: Impensis Thurnisiorum, Fratrum

Bestor TH & Ingram VM (1983) Two DNA methyltransferases from murine erythroleukemia cells: purification, sequence specificity, and mode of interaction with DNA. Proc. Natl. Acad. Sci. U. S. A. 80: 5559–5563

Bettencourt-Dias M & Glover DM (2007) Centrosome biogenesis and function: centrosomics brings new understanding. Nat. Rev. Mol. Cell Biol. 8: 451–463

Beynon RJ, Doherty MK, Pratt JM & Gaskell SJ (2005) Multiplexed absolute quantification in proteomics using artificial QCAT proteins of concatenated signature peptides. Nat. Methods 2: 587–589

Bird A (2002) DNA methylation patterns and epigenetic memory. Genes Dev. 16: 6–21

Bird A (2007) Perceptions of epigenetics. Nature 447: 396–398

Bird AP (1978) Use of restriction enzymes to study eukaryotic DNA methylation: II. The symmetry of methylated sites supports semi-conservative copying of the methylation pattern. J. Mol. Biol. 118: 49–60

Black BE & Bassett EA (2008) The histone variant CENP-A and centromere specification. Curr. Opin. Cell Biol. 20: 91–100

Black BE, Brock MA, Bédard S, Woods VL & Cleveland DW (2007a) An epigenetic mark generated by the incorporation of CENP-A into centromeric nucleosomes. Proc. Natl. Acad. Sci. U. S. A. 104: 5008–5013

Black BE & Cleveland DW (2011) Epigenetic Centromere Propagation and the Nature of CENP-A Nucleosomes. Cell 144: 471–479

Black BE, Foltz DR, Chakravarthy S, Luger K, Woods VL & Cleveland DW (2004) Structural determinants for generating centromeric chromatin. Nature 430: 578–582

Chapter 1

48

Black BE, Jansen LET, Maddox PS, Foltz DR, Desai AB, Shah JV & Cleveland DW (2007b) Centromere identity maintained by nucleosomes assembled with histone H3 containing the CENP-A targeting domain. Mol. Cell 25: 309–322

Blower MD & Karpen GH (2001) The role of Drosophila CID in kinetochore formation, cell-cycle progression and heterochromatin interactions. Nat. Cell Biol. 3: 730–739

Bodor DL, Mata JF, Sergeev M, David AF, Salimian KJ, Panchenko T, Cleveland DW, Black BE, Shah JV & Jansen LET (2014) The quantitative architecture of centromeric chromatin. eLife 3: e02137

Bodor DL, Rodríguez MG, Moreno N & Jansen LET (2012) Analysis of Protein Turnover by Quantitative SNAP-Based Pulse-Chase Imaging. Curr. Protoc. Cell Biol. Chapter 8: Unit8.8

Bodor DL, Valente LP, Mata JF, Black BE & Jansen LET (2013) Assembly in G1 phase and long-term stability are unique intrinsic features of CENP-A nucleosomes. Mol. Biol. Cell 24: 923–932

Boffelli D & Martin DIK (2012) Epigenetic Inheritance: A Contributor to Species Differentiation? DNA Cell Biol. 31: S–11

Brinkley BR & Cartwright J (1975) Cold-Labile and Cold-Stable Microtubules in the Mitotic Spindle of Mammalian Cells*. Ann. N. Y. Acad. Sci. 253: 428–439

Buchwitz BJ, Ahmad K, Moore LL, Roth MB & Henikoff S (1999) Cell division: A histone-H3-like protein in C. elegans. Nature 401: 547–548

Bui M, Dimitriadis EK, Hoischen C, An E, Quénet D, Giebe S, Nita-Lazar A, Diekmann S & Dalal Y (2012) Cell-cycle-dependent structural transitions in the human CENP-A nucleosome in vivo. Cell 150: 317–326

Bukvic N, Susca F, Gentile M, Tangari E, Ianniruberto A & Guanti G (1996) An unusual dicentric Y chromosome with a functional centromere with no detectable alpha-satellite. Hum. Genet. 97: 453–456

Burrack LS, Applen SE & Berman J (2011) The Requirement for the Dam1 Complex Is Dependent upon the Number of Kinetochore Proteins and Microtubules. Curr. Biol. 21: 889–896

Camahort R, Shivaraju M, Mattingly M, Li B, Nakanishi S, Zhu D, Shilatifard A, Workman JL & Gerton JL (2009) Cse4 is part of an octameric nucleosome in budding yeast. Mol. Cell 35: 794–805

Campbell TN & Choy FY (2001) The effect of pH on green fluorescent protein: a brief review. Mol. Biol. Today 2: 1–4

Capozzi O, Purgato S, D’Addabbo P, Archidiacono N, Battaglia P, Baroncini A, Capucci A, Stanyon R, Della Valle G & Rocchi M (2009) Evolutionary descent of a human chromosome 6 neocentromere: a jump back to 17 million years ago. Genome Res. 19: 778–784

Capozzi O, Purgato S, Verdun di Cantogno L, Grosso E, Ciccone R, Zuffardi O, Della Valle G & Rocchi M (2008) Evolutionary and clinical neocentromeres: two faces of the same coin? Chromosoma 117: 339–344


49

Capuano F, Mülleder M, Kok R, Blom HJ & Ralser M (2014) Cytosine DNA Methylation Is Found in Drosophila melanogaster but Absent in Saccharomyces cerevisiae, Schizosaccharomyces pombe, and Other Yeast Species. Anal. Chem. 86: 3697–3702

Carbone L, Nergadze SG, Magnani E, Misceo D, Francesca Cardone M, Roberto R, Bertoni L, Attolini C, et al (2006) Evolutionary movement of centromeres in horse, donkey, and zebra. Genomics 87: 777–782

Cardone MF, Alonso A, Pazienza M, Ventura M, Montemurro G, Carbone L, Jong PJ de, Stanyon R, et al (2006) Independent centromere formation in a capricious, gene-free domain of chromosome 13q21 in Old World monkeys and pigs. Genome Biol. 7: R91

Carroll CW, Milks KJ & Straight AF (2010) Dual recognition of CENP-A nucleosomes is required for centromere assembly. J. Cell Biol. 189: 1143–1155

Carroll CW, Silva MCC, Godek KM, Jansen LET & Straight AF (2009) Centromere assembly requires the direct recognition of CENP-A nucleosomes by CENP-N. Nat. Cell Biol. 11: 896–902

Cavalier-Smith T (2004) The Membranome and Membrane Heredity in Development and Evolution. In Organelles, Genomes and Eukaryote Phylogeny, Hirt RP & Horner DS (eds) pp 335–352. Boca Raton, FL: CRC Press

Chakravarthy S, Park Y-J, Chodaparambil J, Edayathumangalam RS & Luger K (2005) Structure and dynamic properties of nucleosome core particles. FEBS Lett. 579: 895–898

Cheeseman IM, Chappie JS, Wilson-Kubalek EM & Desai A (2006) The conserved KMN network constitutes the core microtubule-binding site of the kinetochore. Cell 127: 983–997

Cheeseman IM & Desai A (2008) Molecular architecture of the kinetochore-microtubule interface. Nat. Rev. Mol. Cell Biol. 9: 33–46

Cheeseman IM, Niessen S, Anderson S, Hyndman F, Yates JR, Oegema K & Desai A (2004) A conserved protein network controls assembly of the outer kinetochore and its ability to sustain tension. Genes Dev. 18: 2255–2268

Chen R-H, Waters JC, Salmon ED & Murray AW (1996) Association of Spindle Assembly Checkpoint Component XMAD2 with Unattached Kinetochores. Science 274: 242–246

Chikashige Y, Kinoshita N, Nakaseko Y, Matsumoto T, Murakami S, Niwa O & Yanagida M (1989) Composite motifs and repeat symmetry in S. pombe centromeres: Direct analysis by integration of Notl restriction sites. Cell 57: 739–751

Chmátal L, Gabriel SI, Mitsainas GP, Martínez-Vargas J, Ventura J, Searle JB, Schultz RM & Lampson MA (2014) Centromere Strength Provides the Cell Biological Basis for Meiotic Drive and Karyotype Evolution in Mice. Curr. Biol. 24: 2295–2300

Cho U-S & Harrison SC (2011) Recognition of the centromere-specific histone Cse4 by the chaperone Scm3. Proc. Natl. Acad. Sci. U. S. A. 108: 9367–9371

Chapter 1

50

Chuang LS, Ian HI, Koh TW, Ng HH, Xu G & Li BF (1997) Human DNA-(cytosine-5) methyltransferase-PCNA complex as a target for p21WAF1. Science 277: 1996–2000

Cimini D, Howell B, Maddox P, Khodjakov A, Degrassi F & Salmon ED (2001) Merotelic Kinetochore Orientation Is a Major Mechanism of Aneuploidy in Mitotic Mammalian Tissue Cells. J. Cell Biol. 153: 517–528

Codomo CA, Furuyama T & Henikoff S (2014) CENP-A octamers do not confer a reduction in nucleosome height by AFM. Nat. Struct. Mol. Biol. 21: 4–5

Coffman VC & Wu J-Q (2012) Counting protein molecules using quantitative fluorescence microscopy. Trends Biochem. Sci. 37: 499–506

Coffman VC, Wu P, Parthun MR & Wu J-Q (2011) CENP-A exceeds microtubule attachment sites in centromere clusters of both budding and fission yeast. J. Cell Biol. 195: 563–572

Colot V & Rossignol J-L (1999) Eukaryotic DNA methylation as an evolutionary device. BioEssays 21: 402–411

Conde e Silva N, Black BE, Sivolob A, Filipski J, Cleveland DW & Prunell A (2007) CENP-A-containing nucleosomes: easier disassembly versus exclusive centromeric localization. J. Mol. Biol. 370: 555–573

Cottarel G, Shero JH, Hieter P & Hegemann JH (1989) A 125-base-pair CEN6 DNA fragment is sufficient for complete meiotic and mitotic centromere functions in Saccharomyces cerevisiae. Mol. Cell. Biol. 9: 3342–3349

Csink AK & Henikoff S (1998) Something from nothing: the evolution and utility of satellite repeats. Trends Genet. TIG 14: 200–204

Cubas P, Vincent C & Coen E (1999) An epigenetic mutation responsible for natural variation in floral symmetry. Nature 401: 157–161

Dalal Y, Wang H, Lindsay S & Henikoff S (2007) Tetrameric structure of centromeric nucleosomes in interphase Drosophila cells. PLoS Biol. 5: e218

Darwin C (1859) On the Origin of Species by Means of Natural Selection Or: The Preservation of Favoured Races in the Struggle for Life. 1st ed. London: J. Murray

Day T & Bonduriansky R (2011) A unified approach to the evolutionary consequences of genetic and nongenetic inheritance. Am. Nat. 178: E18–36

Deichmann U (2004) Early responses to Avery et al.’s paper on DNA as hereditary material. Hist. Stud. Phys. Biol. Sci. 34: 207–232

DeLuca JG, Gall WE, Ciferri C, Cimini D, Musacchio A & Salmon ED (2006) Kinetochore microtubule dynamics and attachment stability are regulated by Hec1. Cell 127: 969–982

Dimitriadis EK, Weber C, Gill RK, Diekmann S & Dalal Y (2010) Tetrameric organization of vertebrate centromeric nucleosomes. Proc. Natl. Acad. Sci. U. S. A. 107: 20317–20322


51

Drané P, Ouararhni K, Depaux A, Shuaib M & Hamiche A (2010) The death-associated protein DAXX is a novel histone chaperone involved in the replication-independent deposition of H3.3. Genes Dev. 24: 1253–1265

Drinnenberg IA, deYoung D, Henikoff S & Malik HS (2014) Recurrent loss of CenH3 is associated with independent transitions to holocentricity in insects. eLife 3: e03676

Dunleavy EM, Almouzni G & Karpen GH (2011) H3.3 is deposited at centromeres in S phase as a placeholder for newly assembled CENP-A in G(1) phase. Nucl. Austin Tex 2: 146–157

Dunleavy EM, Beier NL, Gorgescu W, Tang J, Costes SV & Karpen GH (2012) The Cell Cycle Timing of Centromeric Chromatin Assembly in Drosophila Meiosis Is Distinct from Mitosis Yet Requires CAL1 and CENP-C. PLoS Biol 10: e1001460

Dunleavy EM, Roche D, Tagami H, Lacoste N, Ray-Gallet D, Nakamura Y, Daigo Y, Nakatani Y & Almouzni-Pettinotti G (2009) HJURP is a cell-cycle-dependent maintenance and deposition factor of CENP-A at centromeres. Cell 137: 485–497

Earnshaw WC & Migeon BR (1985) Three related centromere proteins are absent from the inactive centromere of a stable isodicentric chromosome. Chromosoma 92: 290–296

Earnshaw WC & Rothfield N (1985) Identification of a family of human centromere proteins using autoimmune sera from patients with scleroderma. Chromosoma 91: 313–321

Ehrlich M, Gama-Sosa MA, Huang L-H, Midgett RM, Kuo KC, McCune RA & Gehrke C (1982) Amount and distribution of 5-methylcytosine in human DNA from different types of tissues or cells. Nucleic Acids Res. 10: 2709–2721

Erikson EH (1950) Growth and crises of the ‘healthy personality.’ In Symposium on the healthy personality pp 91–146. Oxford, England: Josiah Macy, Jr. Foundation

Fachinetti D, Diego Folco H, Nechemia-Arbely Y, Valente LP, Nguyen K, Wong AJ, Zhu Q, Holland AJ, Desai A, Jansen LET & Cleveland DW (2013) A two-step mechanism for epigenetic specification of centromere identity and function. Nat. Cell Biol. 15: 1056–1066

Fishel B, Amstutz H, Baum M, Carbon J & Clarke L (1988) Structural organization and functional analysis of centromeric DNA in the fission yeast Schizosaccharomyces pombe. Mol. Cell. Biol. 8: 754–763

Flaus A & Owen-Hughes T (2004) Mechanisms for ATP-dependent chromatin remodelling: farewell to the tuna-can octamer? Curr. Opin. Genet. Dev. 14: 165–173

Flemming W (1880) Beiträge zur Kenntniss der Zelle und ihrer Lebenserscheinungen. Theil II. Arch. Für Mikrosk. Anat. 18: 151–259

Flicek P, Amode MR, Barrell D, Beal K, Billis K, Brent S, Carvalho-Silva D, Clapham P, et al (2014) Ensembl 2014. Nucleic Acids Res. 42: D749–D755

Flors C, Hotta J, Uji-i H, Dedecker P, Ando R, Mizuno H, Miyawaki A & Hofkens J (2007) A stroboscopic approach for fast photoactivation-localization microscopy with Dronpa mutants. J. Am. Chem. Soc. 129: 13970–13977

Chapter 1

52

Foltz DR, Jansen LET, Bailey AO, Yates JR, Bassett EA, Wood S, Black BE & Cleveland DW (2009) Centromere-specific assembly of CENP-a nucleosomes is mediated by HJURP. Cell 137: 472–484

Foltz DR, Jansen LET, Black BE, Bailey AO, Yates JR & Cleveland DW (2006) The human CENP-A centromeric nucleosome-associated complex. Nat. Cell Biol. 8: 458–469

Ford-Jones EL & Kellner JD (1995) ‘Cheap torches’: an acronym for congenital and perinatal infections. Pediatr. Infect. Dis. J. 14: 638–639

Fujita Y, Hayashi T, Kiyomitsu T, Toyoda Y, Kokubu A, Obuse C & Yanagida M (2007) Priming of Centromere for CENP-A Recruitment by Human hMis18α, hMis18β, and M18BP1. Dev. Cell 12: 17–30

Furuyama S & Biggins S (2007) Centromere identity is specified by a single centromeric nucleosome in budding yeast. Proc. Natl. Acad. Sci. U. S. A. 104: 14706–14711

Furuyama T, Codomo CA & Henikoff S (2013) Reconstitution of hemisomes on budding yeast centromeric DNA. Nucleic Acids Res.

Furuyama T & Henikoff S (2009) Centromeric nucleosomes induce positive DNA supercoils. Cell 138: 104–113

Gaspar-Maia A, Qadeer ZA, Hasson D, Ratnakumar K, Adrian Leu N, Leroy G, Liu S, Costanzi C, et al (2013) MacroH2A histone variants act as a barrier upon reprogramming towards pluripotency. Nat. Commun. 4: 1565

Gasser SM (2002) Visualizing chromatin dynamics in interphase nuclei. Science 296: 1412–1416

Gassmann R, Rechtsteiner A, Yuen KW, Muroyama A, Egelhofer T, Gaydos L, Barron F, Maddox P, et al (2012) An inverse relationship to germline transcription defines centromeric chromatin in C. elegans. Nature 484: 534–537

Gaudet A & Fitzgerald-Hayes M (1989) Mutations in CEN3 cause aberrant chromosome segregation during meiosis in Saccharomyces cerevisiae. Genetics 121: 477–489

Geoghegan JL & Spencer HG (2012) Population-epigenetic models of selection. Theor. Popul. Biol. 81: 232–242

Gerber SA, Rush J, Stemman O, Kirschner MW & Gygi SP (2003) Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS. Proc. Natl. Acad. Sci. 100: 6940–6945

Goldberg AD, Banaszynski LA, Noh K-M, Lewis PW, Elsaesser SJ, Stadler S, Dewell S, Law M, et al (2010) Distinct factors control histone variant H3.3 localization at specific genomic regions. Cell 140: 678–691

Goldstein LSB & Yang Z (2000) Microtubule-Based Transport Systems in Neurons: The Roles of Kinesins and Dyneins. Annu. Rev. Neurosci. 23: 39–71

Gottschling DE (2004) Summary: Epigenetics—from Phenomenon to Field. Cold Spring Harb. Symp. Quant. Biol. 69: 507–520


53

Goyal R, Reinhardt R & Jeltsch A (2006) Accuracy of DNA methylation pattern preservation by the Dnmt1 methyltransferase. Nucleic Acids Res. 34: 1182–1188

Griesbeck O, Baird GS, Campbell RE, Zacharias DA & Tsien RY (2001) Reducing the environmental sensitivity of yellow fluorescent protein. Mechanism and applications. J. Biol. Chem. 276: 29188–29194

Griffith F (1928) The Significance of Pneumococcal Types. J. Hyg. (Lond.) 27: 113–159

Groth A, Rocha W, Verreault A & Almouzni G (2007) Chromatin challenges during DNA replication and repair. Cell 128: 721–733

Gunzenhäuser J, Olivier N, Pengo T & Manley S (2012) Quantitative Super-Resolution Imaging Reveals Protein Stoichiometry and Nanoscale Morphology of Assembling HIV-Gag Virions. Nano Lett. 12: 4705–4710

Guse A, Carroll CW, Moree B, Fuller CJ & Straight AF (2011) In vitro centromere and kinetochore assembly on defined chromatin templates. Nature 477: 354–358

Haaf T & Willard HF (1997) Chromosome-specific α-satellite DNA from the centromere of chimpanzee chromosome 4. Chromosoma 106: 226–232

Haarhuis JHI, Elbatsh AMO & Rowland BD (2014) Cohesin and Its Regulation: On the Logic of X-Shaped Chromosomes. Dev. Cell 31: 7–18

Haase J, Mishra PK, Stephens A, Haggerty R, Quammen C, Taylor RM 2nd, Yeh E, Basrai MA & Bloom K (2013) A 3D map of the yeast kinetochore reveals the presence of core and accessory centromere-specific histone. Curr. Biol. CB 23: 1939–1944

Habuchi S, Ando R, Dedecker P, Verheijen W, Mizuno H, Miyawaki A & Hofkens J (2005) Reversible single-molecule photoswitching in the GFP-like fluorescent protein Dronpa. Proc. Natl. Acad. Sci. U. S. A. 102: 9511–9516

Hake SB, Garcia BA, Duncan EM, Kauer M, Dellaire G, Shabanowitz J, Bazett-Jones DP, Allis CD & Hunt DF (2006) Expression Patterns and Post-translational Modifications Associated with Mammalian Histone H3 Variants. J. Biol. Chem. 281: 559–568

Halfmann R, Alberti S & Lindquist S (2010) Prions, protein homeostasis, and phenotypic diversity. Trends Cell Biol. 20: 125–133

Halfmann R, Jarosz DF, Jones SK, Chang A, Lancaster AK & Lindquist S (2012) Prions are a common mechanism for phenotypic inheritance in wild yeasts. Nature 482: 363–368

Hardwick KG & Shah JV (2010) Spindle checkpoint silencing: ensuring rapid and concerted anaphase onset. F1000 Biol. Rep. 2: 55

Hasson D, Alonso A, Cheung F, Tepperberg JH, Papenhausen PR, Engelen JJM & Warburton PE (2011) Formation of novel CENP-A domains on tandem repetitive DNA and across chromosome breakpoints on human chromosome 8q21 neocentromeres. Chromosoma 120: 621–632

Hasson D, Panchenko T, Salimian KJ, Salman MU, Sekulic N, Alonso A, Warburton PE & Black BE (2013) The octamer is the major form of CENP-A nucleosomes at human centromeres. Nat. Struct. Mol. Biol. 20: 687–695

Chapter 1

54

Hayden KE (2012) Human centromere genomics: now it’s personal. Chromosome Res. Int. J. Mol. Supramol. Evol. Asp. Chromosome Biol. 20: 621–633

Hayden KE, Strome ED, Merrett SL, Lee H-R, Rudd MK & Willard HF (2013) Sequences Associated with Centromere Competency in the Human Genome. Mol. Cell. Biol. 33: 763–772

Hayden KE & Willard HF (2012) Composition and organization of active centromere sequences in complex genomes. BMC Genomics 13: 324

Hebisch E, Knebel J, Landsberg J, Frey E & Leisner M (2013) High Variation of Fluorescence Protein Maturation Times in Closely Related Escherichia coli Strains. PLoS ONE 8: e75991

Hegemann JH & Fleig UN (1993) The centromere of budding yeast. BioEssays 15: 451–460

Heinrich S, Geissen E-M, Kamenz J, Trautmann S, Widmer C, Drewe P, Knop M, Radde N, Hasenauer J & Hauf S (2013) Determinants of robustness in spindle assembly checkpoint signalling. Nat. Cell Biol. 15: 1328–1339

Hemmerich P, Weidtkamp-Peters S, Hoischen C, Schmiedeberg L, Erliandri I & Diekmann S (2008) Dynamics of inner kinetochore assembly and maintenance in living cells. J. Cell Biol. 180: 1101–1114

Henikoff S, Ahmad K & Malik HS (2001) The Centromere Paradox: Stable Inheritance with Rapidly Evolving DNA. Science 293: 1098–1102

Henikoff S, Ahmad K, Platero JS & Steensel B van (2000) Heterochromatic deposition of centromeric histone H3-like proteins. Proc. Natl. Acad. Sci. 97: 716–721

Henikoff S & Henikoff JG (2012) ‘Point’ Centromeres of Saccharomyces Harbor Single Centromere-Specific Nucleosomes. Genetics 190: 1575–1577

Henikoff S, Ramachandran S, Krassovsky K, Bryson TD, Codomo CA, Brogaard K, Widom J, Wang J-P & Henikoff JG (2014) The budding yeast Centromere DNA Element II wraps a stable Cse4 hemisome in either orientation in vivo. eLife 3: e01861

Hershey AD & Chase M (1952) Independent Functions of Viral Protein and Nucleic Acid in Growth of Bacteriophage. J. Gen. Physiol. 36: 39–56

Heun P, Erhardt S, Blower MD, Weiss S, Skora AD & Karpen GH (2006) Mislocalization of the Drosophila centromere-specific histone CID promotes formation of functional ectopic kinetochores. Dev. Cell 10: 303–315

He Y-F, Li B-Z, Li Z, Liu P, Wang Y, Tang Q, Ding J, Jia Y, et al (2011) Tet-Mediated Formation of 5-Carboxylcytosine and Its Excision by TDG in Mammalian DNA. Science 333: 1303–1307

Hieter P, Pridmore D, Hegemann JH, Thomas M, Davis RW & Philippsen P (1985) Functional selection and analysis of yeast centromeric DNA. Cell 42: 913–921

Higgs HN, Blanchoin L & Pollard TD (1999) Influence of the C Terminus of Wiskott-Aldrich Syndrome Protein (WASp) and the Arp2/3 Complex on Actin Polymerization†. Biochemistry (Mosc.) 38: 15212–15222


55

Hobert O (2011) Maintaining a memory by transcriptional autoregulation. Curr. Biol. 21: R146–R147

Holmberg J & Perlmann T (2012) Maintaining differentiated cellular identity. Nat. Rev. Genet. 13: 429–439

Van Hooser A, Goodrich DW, Allis CD, Brinkley BR & Mancini MA (1998) Histone H3 phosphorylation is required for the initiation, but not maintenance, of mammalian chromosome condensation. J. Cell Sci. 111 ( Pt 23): 3497–3506

Hori T, Shang W-H, Takeuchi K & Fukagawa T (2013) The CCAN recruits CENP-A to the centromere and forms the structural core for kinetochore assembly. J. Cell Biol. 200: 45–60

Howman EV, Fowler KJ, Newson AJ, Redward S, MacDonald AC, Kalitsis P & Choo KHA (2000) Early disruption of centromeric chromatin organization in centromere protein A (Cenpa) null mice. Proc. Natl. Acad. Sci. 97: 1148–1153

Huang B, Wu H, Bhaya D, Grossman A, Granier S, Kobilka BK & Zare RN (2007) Counting Low-Copy Number Proteins in a Single Cell. Science 315: 81–84

Hudson DF, Fowler KJ, Earle E, Saffery R, Kalitsis P, Trowell H, Hill J, Wreford NG, et al (1998) Centromere Protein B Null Mice are Mitotically and Meiotically Normal but Have Lower Body and Testis Weights. J. Cell Biol. 141: 309–319

Hunt CR, Ramnarain D, Horikoshi N, Iyengar P, Pandita RK, Shay JW & Pandita TK (2013) Histone modifications and DNA double-strand break repair after exposure to ionizing radiations. Radiat. Res. 179: 383–392

Ichiyanagi T, Ichiyanagi K, Miyake M & Sasaki H (2013) Accumulation and loss of asymmetric non-CpG methylation during male germ-cell development. Nucleic Acids Res. 41: 738–745

Inoué S & Salmon ED (1995) Force Generation by Microtubule Assembly/Disassembly in Mitosis and Related Movements. Mol. Biol. Cell 6: 1619–1640

Irniger S, Piatti S, Michaelis C & Nasmyth K (1995) Genes involved in sister chromatid separation are needed for b-type cyclin proteolysis in budding yeast. Cell 81: 269–277

Ito S, Shen L, Dai Q, Wu SC, Collins LB, Swenberg JA, He C & Zhang Y (2011) Tet Proteins Can Convert 5-Methylcytosine to 5-Formylcytosine and 5-Carboxylcytosine. Science 333: 1300–1303

Izuta H, Ikeno M, Suzuki N, Tomonaga T, Nozaki N, Obuse C, Kisu Y, Goshima N, Nomura F, Nomura N & Yoda K (2006) Comprehensive analysis of the ICEN (Interphase Centromere Complex) components enriched in the CENP-A chromatin of human cells. Genes Cells 11: 673–684

Jablonka E (2012) Epigenetic variations in heredity and evolution. Clin. Pharmacol. Ther. 92: 683–688

Jablonka E & Lamb MJ (2002) The Changing Concept of Epigenetics. Ann. N. Y. Acad. Sci. 981: 82–96

Chapter 1

56

Jablonka E & Lamb MJ (2005) Evolution in Four Dimensions: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life. Cambridge, MA: MIT Press

Jablonka E & Lamb MJ (2006) The evolution of information in the major transitions. J. Theor. Biol. 239: 236–246

Jablonka E & Raz G (2009) Transgenerational Epigenetic Inheritance: Prevalence, Mechanisms, and Implications for the Study of Heredity and Evolution. Q. Rev. Biol. 84: 131–176

Jackson V (1987) Deposition of newly synthesized histones: new histones H2A and H2B do not deposit in the same nucleosome with new histones H3 and H4. Biochemistry (Mosc.) 26: 2315–2325

Jähner D, Stuhlmann H, Stewart CL, Harbers K, Löhler J, Simon I & Jaenisch R (1982) De novo methylation and expression of retroviral genomes during mouse embryogenesis. Nature 298: 623–628

Jansen LET, Black BE, Foltz DR & Cleveland DW (2007) Propagation of centromeric chromatin requires exit from mitosis. J. Cell Biol. 176: 795–805

Jeltsch A (2002) Beyond Watson and Crick: DNA Methylation and Molecular Enzymology of DNA Methyltransferases. ChemBioChem 3: 274–293

Jenuwein T & Allis CD (2001) Translating the histone code. Science 293: 1074–1080

Jiang D, Liu C, Wang L & Jiang W (2010) Fluorescence single-molecule counting assays for protein quantification using epi-fluorescence microscopy with quantum dots labeling. Anal. Chim. Acta 662: 170–176

Joglekar AP, Bouck DC, Molk JN, Bloom KS & Salmon ED (2006) Molecular architecture of a kinetochore-microtubule attachment site. Nat. Cell Biol. 8: 581–585

Joglekar AP, Bouck D, Finley K, Liu X, Wan Y, Berman J, He X, Salmon ED & Bloom KS (2008) Molecular architecture of the kinetochore-microtubule attachment site is conserved between point and regional centromeres. J. Cell Biol. 181: 587–594

Johannes F, Porcher E, Teixeira FK, Saliba-Colombani V, Simon M, Agier N, Bulski A, Albuisson J, et al (2009) Assessing the Impact of Transgenerational Epigenetic Variation on Complex Traits. PLoS Genet 5: e1000530

Johnston K, Joglekar A, Hori T, Suzuki A, Fukagawa T & Salmon ED (2010) Vertebrate kinetochore protein architecture: protein copy number. J. Cell Biol. 189: 937–943

Kamimura S & Takahashi K (1981) Direct measurement of the force of microtubule sliding in flagella. Nature 293: 566–568

Kasai F, Garcia C, Arruga MV & Ferguson-Smith MA (2003) Chromosome homology between chicken (Gallus gallus domesticus) and the red-legged partridge (Alectoris rufa); evidence of the occurrence of a neocentromere during evolution. Cytogenet. Genome Res. 102: 326–330


57

Kerrebrock AW, Moore DP, Wu JS & Orr-Weaver TL (1995) Mei-S332, a drosophila protein required for sister-chromatid cohesion, can localize to meiotic centromere regions. Cell 83: 247–256

Khare SP, Habib F, Sharma R, Gadewal N, Gupta S & Galande S (2011) HIstome—a relational knowledgebase of human histone proteins and histone modifying enzymes. Nucleic Acids Res.: gkr1125

Kimura H & Cook PR (2001) Kinetics of Core Histones in Living Human Cells Little Exchange of H3 and H4 and Some Rapid Exchange of H2b. J. Cell Biol. 153: 1341–1354

King RW, Peters J-M, Tugendreich S, Rolfe M, Hieter P & Kirschner MW (1995) A 20s complex containing CDC27 and CDC16 catalyzes the mitosis-specific conjugation of ubiquitin to cyclin B. Cell 81: 279–288

Kingston IJ, Yung JSY & Singleton MR (2011) Biophysical Characterization of the Centromere-specific Nucleosome from Budding Yeast. J. Biol. Chem. 286: 4021–4026

Knegt AC, Li S, Engelen JJM, Bijlsma EK & Warburton PE (2003) Prenatal diagnosis of a karyotypically normal pregnancy in a mother with a supernumerary neocentric 13q21 → 13q22 chromosome and balancing reciprocal deletion. Prenat. Diagn. 23: 215–220

Kobayakawa S, Miike K, Nakao M & Abe K (2007) Dynamic changes in the epigenomic state and nuclear organization of differentiating mouse embryonic stem cells. Genes Cells Devoted Mol. Cell. Mech. 12: 447–460

Koppel DE, Axelrod D, Schlessinger J, Elson EL & Webb WW (1976) Dynamics of fluorescence marker concentration as a probe of mobility. Biophys. J. 16: 1315–1329

Kornberg RD (1974) Chromatin Structure: A Repeating Unit of Histones and DNA. Science 184: 868–871

Koshland D & Strunnikov A (1996) Mitotic Chromosome Condensation. Annu. Rev. Cell Dev. Biol. 12: 305–333

Krassovsky K, Henikoff JG & Henikoff S (2012) Tripartite organization of centromeric chromatin in budding yeast. Proc. Natl. Acad. Sci. 109: 243–248

Kunkel TA (2004) DNA Replication Fidelity. J. Biol. Chem. 279: 16895–16898

Lacoste N, Woolfe A, Tachiwana H, Garea AV, Barth T, Cantaloube S, Kurumizaka H, Imhof A & Almouzni G (2014) Mislocalization of the Centromeric Histone Variant CenH3/CENP-A in Human Cells Depends on the Chaperone DAXX. Mol. Cell 53: 631–644

Lagana A, Dorn JF, De Rop V, Ladouceur A-M, Maddox AS & Maddox PS (2010) A small GTPase molecular switch regulates epigenetic centromere maintenance by stabilizing newly incorporated CENP-A. Nat. Cell Biol. 12: 1186–1193

Laird CD, Pleasant ND, Clark AD, Sneeden JL, Hassan KMA, Manley NC, Vary JC, Morgan T, Hansen RS & Stöger R (2004) Hairpin-bisulfite PCR: Assessing epigenetic methylation patterns on complementary strands of individual DNA molecules. Proc. Natl. Acad. Sci. 101: 204–209

Chapter 1

58

Lampson MA & Cheeseman IM (2011) Sensing centromere tension: Aurora B and the regulation of kinetochore function. Trends Cell Biol. 21: 133–140

Lando D, Endesfelder U, Berger H, Subramanian L, Dunne PD, McColl J, Klenerman D, Carr AM, Sauer M, Allshire RC, Heilemann M & Laue ED (2012) Quantitative single-molecule microscopy reveals that CENP-A(Cnp1) deposition occurs during G2 in fission yeast. Open Biol. 2: 120078

Larsen A & Weintraub H (1982) An altered DNA conformation detected by S1 nuclease occurs at specific regions in active chick globin chromatin. Cell 29: 609–622

Law JA & Jacobsen SE (2010) Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nat. Rev. Genet. 11: 204–220

Lawrimore J, Bloom KS & Salmon ED (2011) Point centromeres contain more than a single centromere-specific Cse4 (CENP-A) nucleosome. J. Cell Biol. 195: 573–582

Leake MC, Chandler JH, Wadhams GH, Bai F, Berry RM & Armitage JP (2006) Stoichiometry and turnover in single, functioning membrane protein complexes. Nature 443: 355–358

Lee H-R, Hayden KE & Willard HF (2011) Organization and molecular evolution of CENP-A--associated satellite DNA families in a basal primate genome. Genome Biol. Evol. 3: 1136–1149

Lee H-R, Zhang W, Langdon T, Jin W, Yan H, Cheng Z & Jiang J (2005) Chromatin immunoprecipitation cloning reveals rapid evolutionary patterns of centromeric DNA in Oryza species. Proc. Natl. Acad. Sci. U. S. A. 102: 11793–11798

Lee J-S, Smith E & Shilatifard A (2010) The language of histone crosstalk. Cell 142: 682–685

Liehr T (2014) Small supernumerary marker chromosomes. Available at: http://ssmc-tl.com/sSMC.html [Accessed October 4, 2014]

Liehr T, Kosyakova N, Weise A, Ziegler M & Raabe-Meyer G (2010) First case of a neocentromere formation in an otherwise normal chromosome 7. Cytogenet. Genome Res. 128: 189–191

Li E & Zhang Y (2014) DNA Methylation in Mammals. Cold Spring Harb. Perspect. Biol. 6: a019133

Liu D, Vader G, Vromans MJM, Lampson MA & Lens SMA (2009) Sensing Chromosome Bi-Orientation by Spatial Separation of Aurora B Kinase from Kinetochore Substrates. Science 323: 1350–1353

Liu S-T, Rattner JB, Jablonski SA & Yen TJ (2006) Mapping the assembly pathways that specify formation of the trilaminar kinetochore plates in human cells. J. Cell Biol. 175: 41–53

Li Y & Benezra R (1996) Identification of a Human Mitotic Checkpoint Gene: hsMAD2. Science 274: 246–248

Lochmann B & Ivanov D (2012) Histone H3 Localizes to the Centromeric DNA in Budding Yeast. PLoS Genet 8: e1002739


59

Locke DP, Hillier LW, Warren WC, Worley KC, Nazareth LV, Muzny DM, Yang S-P, Wang Z, et al (2011) Comparative and demographic analysis of orang-utan genomes. Nature 469: 529–533

Losada A, Hirano M & Hirano T (1998) Identification of Xenopus SMC protein complexes required for sister chromatid cohesion. Genes Dev. 12: 1986–1997

Losada A, Yokochi T, Kobayashi R & Hirano T (2000) Identification and Characterization of Sa/Scc3p Subunits in the Xenopus and Human Cohesin Complexes. J. Cell Biol. 150: 405–416

Luger K, Mäder AW, Richmond RK, Sargent DF & Richmond TJ (1997) Crystal structure of the nucleosome core particle at 2.8 A resolution. Nature 389: 251–260

Macdonald PJ, Chen Y & Mueller JD (2012) Chromophore maturation and fluorescence fluctuation spectroscopy of fluorescent proteins in a cell-free expression system. Anal. Biochem. 421: 291–298

Maddox PS, Hyndman F, Monen J, Oegema K & Desai A (2007) Functional genomics identifies a Myb domain-containing protein family required for assembly of CENP-A chromatin. J. Cell Biol. 176: 757–763

Maiti A & Drohat AC (2011) Thymine DNA Glycosylase Can Rapidly Excise 5-Formylcytosine and 5-Carboxylcytosine: Potential Implications for Active Demethylation of CpG Sites. J. Biol. Chem. 286: 35334–35338

Malik HS & Henikoff S (2002) Conflict begets complexity: the evolution of centromeres. Curr. Opin. Genet. Dev. 12: 711–718

Malik HS & Henikoff S (2003) Phylogenomics of the nucleosome. Nat. Struct. Mol. Biol. 10: 882–891

Manuelidis L (1978) Chromosomal localization of complex and simple repeated human DNAs. Chromosoma 66: 23–32

Manuelidis L & Wu JC (1978) Homology between human and simian repeated DNA. Nature 276: 92–94

Marris E, Pearson H, Waldrop M, Hayden EC, Schiermeier Q, Baker M, Brumfiel G & Ledford H (2008) Language: Disputed definitions. Nature 455: 1023–1028

Marshall OJ, Chueh AC, Wong LH & Choo KHA (2008) Neocentromeres: New Insights into Centromere Structure, Disease Development, and Karyotype Evolution. Am. J. Hum. Genet. 82: 261–282

Marshall WF, Vucica Y & Rosenbaum JL (2001) Kinetics and regulation of de novo centriole assembly: Implications for the mechanism of centriole duplication. Curr. Biol. 11: 308–317

Martin DIK, Singer M, Dhahbi J, Mao G, Zhang L, Schroth GP, Pachter L & Boffelli D (2011) Phyloepigenomic comparison of great apes reveals a correlation between somatic and germline methylation states. Genome Res. 21: 2049–2057

Masumoto H, Masukata H, Muro Y, Nozaki N & Okazaki T (1989) A human centromere antigen (CENP-B) interacts with a short specific sequence in alphoid DNA, a human centromeric satellite. J. Cell Biol. 109: 1963–1973

Chapter 1

60

Mayer W, Niveleau A, Walter J, Fundele R & Haaf T (2000) Embryogenesis: Demethylation of the zygotic paternal genome. Nature 403: 501–502

McGrew J, Diehl B & Fitzgerald-Hayes M (1986) Single base-pair mutations in centromere element III cause aberrant chromosome segregation in Saccharomyces cerevisiae. Mol. Cell. Biol. 6: 530–538

McGrew JT, Xiao Z & Fitzgerald-Hayes M (1989) Saccharomyces cerevisiae mutants defective in chromosome segregation. Yeast 5: 271–284

McKinley KL & Cheeseman IM (2014) Polo-like Kinase 1 Licenses CENP-A Deposition at Centromeres. Cell 158: 397–411

McKittrick E, Gafken PR, Ahmad K & Henikoff S (2004) Histone H3.3 is enriched in covalent modifications associated with active chromatin. Proc. Natl. Acad. Sci. U. S. A. 101: 1525–1530

Melters DP, Paliulis LV, Korf IF & Chan SWL (2012) Holocentric chromosomes: convergent evolution, meiotic adaptations, and genomic analysis. Chromosome Res. 20: 579–593

Meluh PB & Koshland D (1995) Evidence that the MIF2 gene of Saccharomyces cerevisiae encodes a centromere protein with homology to the mammalian centromere protein CENP-C. Mol. Biol. Cell 6: 793–807

Meluh PB, Yang P, Glowczewski L, Koshland D & Smith MM (1998) Cse4p Is a Component of the Core Centromere of Saccharomyces cerevisiae. Cell 94: 607–613

Mendel G (1866) Versuche über Pflanzenhybriden. Verhandlungen Naturforschenden Vereines Brünn 4: 3–47

Mendiburo MJ, Padeken J, Fülöp S, Schepers A & Heun P (2011) Drosophila CENH3 is sufficient for centromere formation. Science 334: 686–690

Meselson M & Stahl FW (1958) The replication of DNA in Escherichia coli. Proc. Natl. Acad. Sci. 44: 671–682

Meshorer E & Misteli T (2006) Chromatin in pluripotent embryonic stem cells and differentiation. Nat. Rev. Mol. Cell Biol. 7: 540–546

Meyer-Rochow VB & Gal J (2003) Pressures produced when penguins pooh—calculations on avian defaecation. Polar Biol. 27: 56–58

Michaelis C, Ciosk R & Nasmyth K (1997) Cohesins: Chromosomal Proteins that Prevent Premature Separation of Sister Chromatids. Cell 91: 35–45

Miell MDD, Fuller CJ, Guse A, Barysz HM, Downes A, Owen-Hughes T, Rappsilber J, Straight AF & Allshire RC (2013) CENP-A confers a reduction in height on octameric nucleosomes. Nat. Struct. Mol. Biol. 20: 763–765

Miell MDD, Straight AF & Allshire RC (2014) Reply to ‘CENP-A octamers do not confer a reduction in nucleosome height by AFM’. Nat. Struct. Mol. Biol. 21: 5–8

Miga KH, Newton Y, Jain M, Altemose N, Willard HF & Kent WJ (2014) Centromere reference models for human chromosomes X and Y satellite arrays. Genome Res. 24: 697–707


61

Mitchison T, Evans L, Schulze E & Kirschner M (1986) Sites of microtubule assembly and disassembly in the mitotic spindle. Cell 45: 515–527

Mito Y, Henikoff JG & Henikoff S (2005) Genome-scale profiling of histone H3.3 replacement patterns. Nat. Genet. 37: 1090–1097

Mizuguchi G, Xiao H, Wisniewski J, Smith MM & Wu C (2007) Nonhistone Scm3 and histones CenH3-H4 assemble the core of centromere-specific nucleosomes. Cell 129: 1153–1164

Montefalcone G, Tempesta S, Rocchi M & Archidiacono N (1999) Centromere Repositioning. Genome Res. 9: 1184–1188

Moran NA, McCutcheon JP & Nakabachi A (2008) Genomics and evolution of heritable bacterial symbionts. Annu. Rev. Genet. 42: 165–190

Morse C (2013) Seven Ways to Fit More Stuff in Your Suitcase. SmarterTravel.com Available at: http://www.smartertravel.com/photo-galleries/editorial/seven-ways-to-fit-more-stuff-in-your-suitcase.html?id=620&source=41718 [Accessed September 30, 2014]

Mousson F, Ochsenbein F & Mann C (2007) The histone chaperone Asf1 at the crossroads of chromatin and DNA checkpoint pathways. Chromosoma 116: 79–93

Müller S, Montes de Oca R, Lacoste N, Dingli F, Loew D & Almouzni G (2014) Phosphorylation and DNA Binding of HJURP Determine Its Centromeric Recruitment and Function in CenH3CENP-A Loading. Cell Rep. 8: 190–203

Muramoto T, Müller I, Thomas G, Melvin A & Chubb JR (2010) Methylation of H3K4 Is required for inheritance of active transcriptional states. Curr. Biol. CB 20: 397–406

Nagaki K, Cheng Z, Ouyang S, Talbert PB, Kim M, Jones KM, Henikoff S, Buell CR & Jiang J (2004) Sequencing of a rice centromere uncovers active genes. Nat. Genet. 36: 138–145

Nasmyth K & Haering CH (2009) Cohesin: Its Roles and Mechanisms. Annu. Rev. Genet. 43: 525–558

Ng HH, Robert F, Young RA & Struhl K (2003) Targeted recruitment of Set1 histone methylase by elongating Pol II provides a localized mark and memory of recent transcriptional activity. Mol. Cell 11: 709–719

Ng RK & Gurdon JB (2008) Epigenetic memory of an active gene state depends on histone H3.3 incorporation into chromatin in the absence of transcription. Nat. Cell Biol. 10: 102–109

Niedenthal R, Stoll R & Hegemann JH (1991) In vivo characterization of the Saccharomyces cerevisiae centromere DNA element I, a binding site for the helix-loop-helix protein CPF1. Mol. Cell. Biol. 11: 3545–3553

Nigg EA & Stearns T (2011) The centrosome cycle: Centriole biogenesis, duplication and inherent asymmetries. Nat. Cell Biol. 13: 1154–1160

Ohzeki J, Nakano M, Okada T & Masumoto H (2002) CENP-B box is required for de novo centromere chromatin assembly on human alphoid DNA. J. Cell Biol. 159: 765–775

Chapter 1

62

Okada M, Cheeseman IM, Hori T, Okawa K, McLeod IX, Yates JR 3rd, Desai A & Fukagawa T (2006) The CENP-H-I complex is required for the efficient incorporation of newly synthesized CENP-A into centromeres. Nat. Cell Biol. 8: 446–457

Okano M, Bell DW, Haber DA & Li E (1999) DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development. Cell 99: 247–257

Okano M, Xie S & Li E (1998) Cloning and characterization of a family of novel mammalian DNA (cytosine-5) methyltransferases. Nat. Genet. 19: 219–220

Olins AL & Olins DE (1974) Spheroid Chromatin Units (ν Bodies). Science 183: 330–332

Ooi SKT & Bestor TH (2008) The colorful history of active DNA demethylation. Cell 133: 1145–1148

Oswald J, Engemann S, Lane N, Mayer W, Olek A, Fundele R, Dean W, Reik W & Walter J (2000) Active demethylation of the paternal genome in the mouse zygote. Curr. Biol. 10: 475–478

Padeganeh A, Ryan J, Boisvert J, Ladouceur A-M, Dorn JF & Maddox PS (2013) Octameric CENP-A nucleosomes are present at human centromeres throughout the cell cycle. Curr. Biol. CB 23: 764–769

Palmer DK, O’Day K & Margolis RL (1990) The centromere specific histone CENP-A is selectively retained in discrete foci in mammalian sperm nuclei. Chromosoma 100: 32–36

Palmer DK, O’Day K, Trong HL, Charbonneau H & Margolis RL (1991) Purification of the centromere-specific protein CENP-A and demonstration that it is a distinctive histone. Proc. Natl. Acad. Sci. U. S. A. 88: 3734–3738

Palmer DK, O’Day K, Wener MH, Andrews BS & Margolis RL (1987) A 17-kD centromere protein (CENP-A) copurifies with nucleosome core particles and with histones. J. Cell Biol. 104: 805–815

Pardo-Manuel de Villena F de & Sapienza C (2001a) Transmission ratio distortion in offspring of heterozygous female carriers of Robertsonian translocations. Hum. Genet. 108: 31–36

Pardo-Manuel de Villena F & Sapienza C (2001b) Female meiosis drives karyotypic evolution in mammals. Genetics 159: 1179–1189

Pasque V, Gillich A, Garrett N & Gurdon JB (2011) Histone variant macroH2A confers resistance to nuclear reprogramming. EMBO J. 30: 2373–2387

Perpelescu M, Nozaki N, Obuse C, Yang H & Yoda K (2009) Active establishment of centromeric CENP-A chromatin by RSF complex. J. Cell Biol. 185: 397–407

Pinsky BA, Kung C, Shokat KM & Biggins S (2006) The Ipl1-Aurora protein kinase activates the spindle checkpoint by creating unattached kinetochores. Nat. Cell Biol. 8: 78–83

Piras FM, Nergadze SG, Magnani E, Bertoni L, Attolini C, Khoriauli L, Raimondi E & Giulotto E (2010) Uncoupling of Satellite DNA and Centromeric Function in the Genus Equus. PLoS Genet 6: e1000845


63

Pluta AF, Saitoh N, Goldberg I & Earnshaw WC (1992) Identification of a subdomain of CENP-B that is necessary and sufficient for localization to the human centromere. J. Cell Biol. 116: 1081–1093

Ponger L & Li W-H (2005) Evolutionary Diversification of DNA Methyltransferases in Eukaryotic Genomes. Mol. Biol. Evol. 22: 1119–1128

Prince CG & Demiris Y (2003) Editorial: Introduction to the Special Issue on Epigenetic Robotics. Adapt. Behav. 11: 75–77

Probst AV & Almouzni G (2008) Pericentric heterochromatin: dynamic organization during early development in mammals. Differentiation 76: 15–23

Prusiner SB (1982) Novel proteinaceous infectious particles cause scrapie. Science 216: 136–144

Prusiner SB (1998) Prions. Proc. Natl. Acad. Sci. U. S. A. 95: 13363–13383

Pryde FE & Louis EJ (1999) Limitations of silencing at native yeast telomeres. EMBO J. 18: 2538–2550

Ptashne M (2013) Epigenetics: Core misconcept. Proc. Natl. Acad. Sci. 110: 7101–7103

Ramsahoye BH, Biniszkiewicz D, Lyko F, Clark V, Bird AP & Jaenisch R (2000) Non-CpG methylation is prevalent in embryonic stem cells and may be mediated by DNA methyltransferase 3a. Proc. Natl. Acad. Sci. 97: 5237–5242

Raychaudhuri N, Dubruille R, Orsi GA, Bagheri HC, Loppin B & Lehner CF (2012) Transgenerational propagation and quantitative maintenance of paternal centromeres depends on Cid/Cenp-A presence in Drosophila sperm. PLoS Biol. 10: e1001434

Ray-Gallet D, Quivy J-P, Scamps C, Martini EM-D, Lipinski M & Almouzni G (2002) HIRA is critical for a nucleosome assembly pathway independent of DNA synthesis. Mol. Cell 9: 1091–1100

Raynaud C, Mallory AC, Latrasse D, Jégu T, Bruggeman Q, Delarue M, Bergounioux C & Benhamed M (2014) Chromatin meets the cell cycle. J. Exp. Bot.: ert433

Rechavi O, Minevich G & Hobert O (2011) Transgenerational Inheritance of an Acquired Small RNA-Based Antiviral Response in C. elegans. Cell 147: 1248–1256

Reeves R (1992) Chromatin changes during the cell cycle. Curr. Opin. Cell Biol. 4: 413–423

Régnier V, Vagnarelli P, Fukagawa T, Zerjal T, Burns E, Trouche D, Earnshaw W & Brown W (2005) CENP-A is required for accurate chromosome segregation and sustained kinetochore association of BubR1. Mol. Cell. Biol. 25: 3967–3981

Reik W, Dean W & Walter J (2001) Epigenetic reprogramming in mammalian development. Science 293: 1089–1093

Ribeiro SA, Vagnarelli P, Dong Y, Hori T, McEwen BF, Fukagawa T, Flors C & Earnshaw WC (2010) A super-resolution map of the vertebrate kinetochore. Proc. Natl. Acad. Sci. U. S. A. 107: 10484–10489

Rocchi M, Archidiacono N, Schempp W, Capozzi O & Stanyon R (2012) Centromere repositioning in mammals. Heredity 108: 59–67

Chapter 1

64

Rodrigues-Martins A, Riparbelli M, Callaini G, Glover DM & Bettencourt-Dias M (2007) Revisiting the Role of the Mother Centriole in Centriole Biogenesis. Science 316: 1046–1050

Rodrigues-Martins A, Riparbelli M, Callaini G, Glover DM & Bettencourt-Dias M (2008) From centriole biogenesis to cellular function: Centrioles are essential for cell division at critical developmental stages. Cell Cycle 7: 11–16

Rogakou EP, Boon C, Redon C & Bonner WM (1999) Megabase Chromatin Domains Involved in DNA Double-Strand Breaks in Vivo. J. Cell Biol. 146: 905–916

Rosenfeld N, Young JW, Alon U, Swain PS & Elowitz MB (2005) Gene regulation at the single-cell level. Science 307: 1962–1965

Rosenfeld S (2011) Critical Self-Organized Self-Sustained Oscillations in Large Regulatory Networks: Towards Understanding the Gene Expression Initiation. Gene Regul. Syst. Biol.: 27

Rothbart SB & Strahl BD (2014) Interpreting the language of histone and DNA modifications. Biochim. Biophys. Acta BBA - Gene Regul. Mech. 1839: 627–643

Sacristan C & Kops GJPL (2015) Joined at the hip: kinetochores, microtubules, and spindle assembly checkpoint signaling. Trends Cell Biol. 25: 21–28

Salic A, Waters JC & Mitchison TJ (2004) Vertebrate Shugoshin Links Sister Centromere Cohesion and Kinetochore Microtubule Stability in Mitosis. Cell 118: 567–578

Salmon ED, Goode D, Maugel TK & Bonar DB (1976) Pressure-induced depolymerization of spindle microtubules. III. Differential stability in HeLa cells. J. Cell Biol. 69: 443–454

Santillan M, Mackey MC & Zeron ES (2007) Origin of Bistability in the lac Operon. Biophys. J. 92: 3830–3842

Sawatsubashi S, Murata T, Lim J, Fujiki R, Ito S, Suzuki E, Tanabe M, Zhao Y, et al (2010) A histone chaperone, DEK, transcriptionally coactivates a nuclear receptor. Genes Dev. 24: 159–170

Schittenhelm RB, Althoff F, Heidmann S & Lehner CF (2010) Detrimental incorporation of excess Cenp-A/Cid and Cenp-C into Drosophila centromeres is prevented by limiting amounts of the bridging factor Cal1. J. Cell Sci. 123: 3768–3779

Schrader F (1935) Notes on the Mitotic Behavior of Long Chromosomes. Cytologia (Tokyo) 6: 422–430

Schuh M, Lehner CF & Heidmann S (2007) Incorporation of Drosophila CID/CENP-A and CENP-C into centromeres during early embryonic anaphase. Curr. Biol. CB 17: 237–243

Schutz-Geschwender A, Zhang Y, Holt T, McDermitt D & Olive DM (2004) Quantitative, two-color Western blot detection with infrared fluorescence Available at: http://cdn.licor.com/bio/PDF/IRquant.pdf [Accessed October 30, 2013]

Schwille P (2001) Fluorescence correlation spectroscopy and its potential for intracellular applications. Cell Biochem. Biophys. 34: 383–408


65

Sclafani RA & Holzen TM (2007) Cell Cycle Regulation of DNA Replication. Annu. Rev. Genet. 41: 237–280

Scoville AG, Barnett LL, Bodbyl-Roels S, Kelly JK & Hileman LC (2011) Differential regulation of a MYB transcription factor is correlated with transgenerational epigenetic inheritance of trichome density in Mimulus guttatus. New Phytol. 191: 251–263

Sekulic N, Bassett EA, Rogers DJ & Black BE (2010) The structure of (CENP-A-H4)(2) reveals physical features that mark centromeres. Nature 467: 347–351

Shang W-H, Hori T, Toyoda A, Kato J, Popendorf K, Sakakibara Y, Fujiyama A & Fukagawa T (2010) Chickens possess centromeres with both extended tandem repeats and short non-tandem-repetitive sequences. Genome Res. 20: 1219–1228

Sharif J, Muto M, Takebayashi S, Suetake I, Iwamatsu A, Endo TA, Shinga J, Mizutani-Koseki Y, et al (2007) The SRA protein Np95 mediates epigenetic inheritance by recruiting Dnmt1 to methylated DNA. Nature 450: 908–912

Shea N (2009) Imitation as an inheritance system. Philos. Trans. R. Soc. B Biol. Sci. 364: 2429–2443

Shelby RD, Vafa O & Sullivan KF (1997) Assembly of CENP-A into centromeric chromatin requires a cooperative array of nucleosomal DNA contact sites. J. Cell Biol. 136: 501–513

Shivaraju M, Unruh JR, Slaughter BD, Mattingly M, Berman J & Gerton JL (2012) Cell-Cycle-Coupled Structural Oscillation of Centromeric Nucleosomes in Yeast. Cell 150: 304–316

Shorter J & Lindquist S (2005) Prions as adaptive conduits of memory and inheritance. Nat. Rev. Genet. 6: 435–450

Shuaib M, Ouararhni K, Dimitrov S & Hamiche A (2010) HJURP binds CENP-A via a highly conserved N-terminal domain and mediates its deposition at centromeres. Proc. Natl. Acad. Sci. U. S. A. 107: 1349–1354

Siegel TN, Hekstra DR, Kemp LE, Figueiredo LM, Lowell JE, Fenyo D, Wang X, Dewell S & Cross GAM (2009) Four histone variants mark the boundaries of polycistronic transcription units in Trypanosoma brucei. Genes Dev. 23: 1063–1076

Silva MCC, Bodor DL, Stellfox ME, Martins NMC, Hochegger H, Foltz DR & Jansen LET (2012) Cdk activity couples epigenetic centromere inheritance to cell cycle progression. Dev. Cell 22: 52–63

Sinsheimer RL (1955) The Action of Pancreatic Deoxyribonuclease Ii. Isomeric Dinucleotides. J. Biol. Chem. 215: 579–583

Smith S & Stillman B (1989) Purification and characterization of CAF-I, a human cell factor required for chromatin assembly during DNA replication in vitro. Cell 58: 15–25

Song L, Zhang Z, Grasfeder LL, Boyle AP, Giresi PG, Lee B-K, Sheffield NC, Graf S, et al (2011) Open chromatin defined by DNaseI and FAIRE identifies regulatory elements that shape cell-type identity. Genome Res. 21: 1757–1767

Chapter 1

66

Sonneborn TM (1964) The Differentiation of Cells. Proc. Natl. Acad. Sci. 51: 915–929

Soshnikova N & Duboule D (2009) Epigenetic temporal control of mouse Hox genes in vivo. Science 324: 1320–1323

Stern S, Fridmann-Sirkis Y, Braun E & Soen Y (2012) Epigenetically heritable alteration of fly development in response to toxic challenge. Cell Rep. 1: 528–542

Stewart CL, Stuhlmann H, Jähner D & Jaenisch R (1982) De novo methylation, expression, and infectivity of retroviral genomes introduced into embryonal carcinoma cells. Proc. Natl. Acad. Sci. 79: 4098–4102

Stoler S, Keith KC, Curnick KE & Fitzgerald-Hayes M (1995) A mutation in CSE4, an essential gene encoding a novel chromatin-associated protein in yeast, causes chromosome nondisjunction and cell cycle arrest at mitosis. Genes Dev. 9: 573–586

Strahl BD & Allis CD (2000) The language of covalent histone modifications. Nature 403: 41–45

Sudakin V, Ganoth D, Dahan A, Heller H, Hershko J, Luca FC, Ruderman JV & Hershko A (1995) The cyclosome, a large complex containing cyclin-selective ubiquitin ligase activity, targets cyclins for destruction at the end of mitosis. Mol. Biol. Cell 6: 185–197

Suhling K, Siegel J, Phillips D, French PMW, Lévêque-Fort S, Webb SED & Davis DM (2002) Imaging the Environment of Green Fluorescent Protein. Biophys. J. 83: 3589–3595

Sullivan KF, Hechenberger M & Masri K (1994) Human CENP-A contains a histone H3 related histone fold domain that is required for targeting to the centromere. J. Cell Biol. 127: 581–592

Sullivan SA, Aravind L, Makalowska I, Baxevanis AD & Landsman D (2000) The Histone Database: a comprehensive WWW resource for histones and histone fold-containing proteins. Nucleic Acids Res. 28: 320–322

Sullivan S, Sink DW, Trout KL, Makalowska I, Taylor PM, Baxevanis AD & Landsman D (2002) The Histone Database. Nucleic Acids Res. 30: 341–342

Sun X, Wahlstrom J & Karpen G (1997) Molecular Structure of a Functional Drosophila Centromere. Cell 91: 1007–1019

Tachiwana H, Kagawa W, Shiga T, Osakabe A, Miya Y, Saito K, Hayashi-Takanaka Y, Oda T, Sato M, Park S-Y, Kimura H & Kurumizaka H (2011) Crystal structure of the human centromeric nucleosome containing CENP-A. Nature 476: 232–235

Tagami H, Ray-Gallet D, Almouzni G & Nakatani Y (2004) Histone H3.1 and H3.3 complexes mediate nucleosome assembly pathways dependent or independent of DNA synthesis. Cell 116: 51–61

Tahiliani M, Koh KP, Shen Y, Pastor WA, Bandukwala H, Brudno Y, Agarwal S, Iyer LM, Liu DR, Aravind L & Rao A (2009) Conversion of 5-Methylcytosine to 5-Hydroxymethylcytosine in Mammalian DNA by MLL Partner TET1. Science 324: 930–935


67

Talbert PB, Ahmad K, Almouzni G, Ausió J, Berger F, Bhalla PL, Bonner WM, Cande WZ, et al (2012) A unified phylogeny-based nomenclature for histone variants. Epigenetics Chromatin 5: 7

Talbert PB, Masuelli R, Tyagi AP, Comai L & Henikoff S (2002) Centromeric Localization and Adaptive Evolution of an Arabidopsis Histone H3 Variant. Plant Cell Online 14: 1053–1066

Tal O, Kisdi E & Jablonka E (2010) Epigenetic Contribution to Covariance Between Relatives. Genetics 184: 1037–1050

Terra SL, English CN, Hergert P, McEwen BF, Sluder G & Khodjakov A (2005) The de novo centriole assembly pathway in HeLa cells cell cycle progression and centriole assembly/maturation. J. Cell Biol. 168: 713–722

The Nucleus and DNA Replication (2015) Hum. Anat. Physiol. Available at: http://philschatz.com/anatomy-book/contents/m46073.html [Accessed January 9, 2015]

Thoma F, Koller T & Klug A (1979) Involvement of histone H1 in the organization of the nucleosome and of the salt-dependent superstructures of chromatin. J. Cell Biol. 83: 403–427

Turner BM (2002) Cellular memory and the histone code. Cell 111: 285–291

Tyler-Smith C, Gimelli G, Giglio S, Floridia G, Pandya A, Terzoli G, Warburton PE, Earnshaw WC & Zuffardi O (1999) Transmission of a Fully Functional Human Neocentromere through Three Generations. Am. J. Hum. Genet. 64: 1440–1444

Uhlmann F, Lottspeich F & Nasmyth K (1999) Sister-chromatid separation at anaphase onset is promoted by cleavage of the cohesin subunit Scc1. Nature 400: 37–42

Uhlmann F & Nasmyth K (1998) Cohesion between sister chromatids must be established during DNA replication. Curr. Biol. CB 8: 1095–1101

Uhlmann F, Wernic D, Poupart MA, Koonin EV & Nasmyth K (2000) Cleavage of cohesin by the CD clan protease separin triggers anaphase in yeast. Cell 103: 375–386

Ulbrich MH & Isacoff EY (2007) Subunit counting in membrane-bound proteins. Nat. Methods 4: 319–321

Ventura M, Mudge JM, Palumbo V, Burn S, Blennow E, Pierluigi M, Giorda R, Zuffardi O, Archidiacono N, Jackson MS & Rocchi M (2003) Neocentromeres in 15q24-26 map to duplicons which flanked an ancestral centromere in 15q25. Genome Res. 13: 2059–2068

Ventura M, Weigl S, Carbone L, Cardone MF, Misceo D, Teti M, D’Addabbo P, Wandall A, et al (2004) Recurrent Sites for New Centromere Seeding. Genome Res. 14: 1696–1703

Voullaire LE, Slater HR, Petrovic V & Choo KH (1993) A functional marker centromere with no detectable alpha-satellite, satellite III, or CENP-B protein: activation of a latent centromere? Am. J. Hum. Genet. 52: 1153–1163

Waddington CH (1942) The epigenotype. Endeavour 1: 18–20

Chapter 1

68

Wade CM, Giulotto E, Sigurdsson S, Zoli M, Gnerre S, Imsland F, Lear TL, Adelson DL, et al (2009) Genome Sequence, Comparative Analysis, and Population Genetics of the Domestic Horse. Science 326: 865–867

Waizenegger IC, Hauf S, Meinke A & Peters J-M (2000) Two Distinct Pathways Remove Mammalian Cohesin from Chromosome Arms in Prophase and from Centromeres in Anaphase. Cell 103: 399–410

Walkiewicz MP, Dimitriadis EK & Dalal Y (2014) CENP-A octamers do not confer a reduction in nucleosome height by AFM. Nat. Struct. Mol. Biol. 21: 2–3

Wandall A, Tranebjærg L & Tommerup N (1998) A neocentromere on human chromosome 3 without detectable α-satellite DNA forms morphologically normal kinetochores. Chromosoma 107: 359–365

Wang J, Liu X, Dou Z, Chen L, Jiang H, Fu C, Fu G, Liu D, et al (2014) Mitotic Regulator Mis18β Interacts with and Specifies the Centromeric Assembly of Molecular Chaperone Holliday Junction Recognition Protein (HJURP). J. Biol. Chem. 289: 8326–8336

Wang YV, Wade M, Wong E, Li Y-C, Rodewald LW & Wahl GM (2007) Quantitative analyses reveal the importance of regulated Hdmx degradation for P53 activation. Proc. Natl. Acad. Sci. 104: 12365–12370

Warburton PE, Cooke CA, Bourassa S, Vafa O, Sullivan BA, Stetten G, Gimelli G, Warburton D, Tyler-Smith C, Sullivan KF, Poirier GG & Earnshaw WC (1997) Immunolocalization of CENP-A suggests a distinct nucleosome structure at the inner kinetochore plate of active centromeres. Curr. Biol. CB 7: 901–904

Warren G & Wickner W (1996) Organelle Inheritance. Cell 84: 395–400

Waters JC, Chen RH, Murray AW & Salmon ED (1998) Localization of Mad2 to kinetochores depends on microtubule attachment, not tension. J. Cell Biol. 141: 1181–1191

Watson JD & Crick FH (1953a) Molecular structure of nucleic acids; a structure for deoxyribose nucleic acid. Nature 171: 737–738

Watson JD & Crick FH (1953b) Genetical implications of the structure of deoxyribonucleic acid. Nature 171: 964–967

Weidemann T & Schwille P (2009) Fluorescence Correlation Spectroscopy in Living Cells. In Handbook of Single-Molecule Biophysics, Hinterdorfer P & Oijen A (eds) pp 217–241. New York, NY: Springer US

Wiedemann SM, Mildner SN, Bönisch C, Israel L, Maiser A, Matheisl S, Straub T, Merkl R, Leonhardt H, Kremmer E, Schermelleh L & Hake SB (2010) Identification and characterization of two novel primate-specific histone H3 variants, H3.X and H3.Y. J. Cell Biol. 190: 777–791

Willard HF (1990) Centromeres of mammalian chromosomes. Trends Genet. TIG 6: 410–416

Willard HF & Waye JS (1987) Hierarchical order in chromosome-specific human alpha satellite DNA. Trends Genet. 3: 192–198


69

Williams JS, Hayashi T, Yanagida M & Russell P (2009) Fission yeast Scm3 mediates stable assembly of Cnp1/CENP-A into centromeric chromatin. Mol. Cell 33: 287–298

Wisniewski J, Hajj B, Chen J, Mizuguchi G, Xiao H, Wei D, Dahan M & Wu C (2014) Imaging the fate of histone Cse4 reveals de novo replacement in S phase and subsequent stable residence at centromeres. eLife 3: e02203

Woodcock CL & Ghosh RP (2010) Chromatin Higher-order Structure and Dynamics. Cold Spring Harb. Perspect. Biol. 2: a000596

Wu C, M. Bingham P, Livak KJ, Holmgren R & Elgin SCR (1979) The chromatin structure of specific genes: I. Evidence for higher order domains of defined DNA sequence. Cell 16: 797–806

Wu J-Q, McCormick CD & Pollard TD (2008) Chapter 9: Counting proteins in living cells by quantitative fluorescence microscopy with internal standards. Methods Cell Biol. 89: 253–273

Wu J-Q & Pollard TD (2005) Counting cytokinesis proteins globally and locally in fission yeast. Science 310: 310–314

Yoda K, Ando S, Morishita S, Houmura K, Hashimoto K, Takeyasu K & Okazaki T (2000) Human centromere protein A (CENP-A) can replace histone H3 in nucleosome reconstitution in vitro. Proc. Natl. Acad. Sci. U. S. A. 97: 7266–7271

Zhang W, Colmenares SU & Karpen GH (2012) Assembly of Drosophila centromeric nucleosomes requires CID dimerization. Mol. Cell 45: 263–269

Zur A & Brandeis M (2001) Securin degradation is mediated by fzy and fzr, and is required for complete chromatid separation but not for cytokinesis. EMBO J. 20: 792–801

CHAPTER 2

Analysis of Protein Turnover by Quantitative SNAP-

Based Pulse-Chase Imaging

Dani L. Bodor, Mariluz Gómez Rodríguez, Nuno Moreno, and Lars E.T. Jansen


NB: This chapter is a near literal transcription of Current Protocols in Cell Biology.

55:8.8:8.8.1–8.8.34.

ABSTRACT

Assessment of protein dynamics in living cells is crucial for

understanding their biological properties and function. The SNAP-tag, a

self-labeling suicide enzyme presents a tool with unique features that can be

adopted for determining protein dynamics in living cells. Here we present

detailed protocols for the use of SNAP in fluorescent pulse-chase and

quench-chase-pulse experiments. These time slicing methods provide

powerful tools to assay and quantify the fate and turnover rate of proteins of

different ages. We cover advantages and pitfalls of SNAP-tagging in fixed

and live cell studies and evaluate the recently developed fast acting SNAPf

variant. In addition, to facilitate the analysis of protein turnover datasets, we

present an automated algorithm for spot recognition and quantification.

Fluoresent pulse-chase imaging and quantification

73

INTRODUCTION

The ability to track specific populations of proteins over time in living

cells is essential to gain insight into the dynamics of cellular processes. An

array of methodologies exists that assess different aspects of protein

dynamics in living cells. These include fluorescence recovery after

photobleaching (FRAP), photoactivation, and recombination induced tag

exchange (see Table 2.1 for a more extensive list).

Here we discuss SNAP-based pulse-chase imaging, a powerful method to

track protein dynamics with distinct advantages over traditional methods to

assess protein dynamics. SNAP is a suicide enzyme protein fusion tag that

catalyzes its own covalent binding to the cell permeable molecule

benzylguanine (BG), and (fluorescent) derivatives thereof (Figure 2.1;

Damoiseaux et al, 2001; Keppler et al, 2003, 2004). Fusion of SNAP to a

protein of interest allows this protein to be (fluorescently) labeled at will in

living cells. Importantly, subsequent removal of the substrate results in the

specific labeling of the initial pulse labeled pool. Changes in location and

turnover of this pool can be determined and quantified. Moreover, serial

labeling of SNAP-tagged proteins with different SNAP substrates

distinguishes proteins synthesized at different times, such that “old” and

“new” pools can be detected separately (Figure 2.3A and Jansen et al, 2007).

Figure 2.1 Principle of SNAP pulse labeling. SNAP is cloned as an epitope tag to a protein of interest. Reaction of SNAP

fusion proteins with benzylguanine (or labeled derivatives) results in a covalent irreversible bond between the (labeled)

benzyl moiety and a reactive cysteine in SNAP.

Chapter 2

74

Table 2.1 Methods to Analyze Protein Turnover

Sho

rt d

escr

ipti

on

Ad

van

tage

sD

isad

van

tage

sEx

amp

les

Re

fere

nce

s

Flu

ore

scen

ce R

eco

very

Aft

er

Ph

oto

ble

ach

ing

(FR

AP

)

Mea

sure

s lo

cal p

rote

in t

urn

ove

r

(tim

e &

ext

en

t) a

fte

r

ph

oto

ble

ach

ing

Allo

ws

anal

ysis

at

very

sh

ort

tim

esca

les

(min

ute

s-se

con

ds)

No

t p

oss

ible

at

lon

g ti

mes

cale

s

(ho

urs

-day

s), c

ell b

y ce

ll an

alys

isFR

AP

, FLI

Pre

view

ed

in: L

ipp

inco

tt-S

chw

artz

et

al,

20

01

Flu

ore

scen

ce C

orr

elat

ion

Spec

tro

sco

py

(FC

S)

Mea

sure

s d

iffu

sio

n o

f fl

uo

resc

en

t

pro

tein

s in

a v

ery

smal

l vo

lum

e

Allo

ws

accu

rate

det

erm

inat

ion

of

pro

tein

co

nce

trat

ion

s an

d d

iffu

sio

n

rate

s; s

ingl

e m

ole

cule

sen

siti

ty

On

ly w

ork

s fo

r m

ob

ile p

rote

ins

at

low

co

nce

ntr

atio

ns;

req

uir

es h

igh

ly

spec

ializ

ed e

qu

ipm

ent

FCS,

FC

CS,

RIC

Sre

view

ed

in: L

ipp

inco

tt-S

chw

artz

et

al,

20

01

Ph

oto

-act

ivat

able

flu

ore

scen

t p

rote

ins

(PA

FPs)

Flu

ore

sce

nt

pro

tein

s th

at c

an b

e

"tu

rned

on

" b

y la

ser

acti

vati

on

Allo

ws

anal

ysis

of

a sp

ecif

ic

sub

cellu

lar

po

ol o

f p

rote

in

Flu

ore

sce

nce

pri

or

to a

ctiv

atio

n;

req

uir

es c

ell

by

cell

acti

vati

on

Dro

np

a, P

adro

n,

bsD

ron

pa,

PA

-GFP

,

PA

mC

her

ry

revi

ewe

d in

: Lu

kyan

ov

et

al, 2

00

5

Ph

oto

-co

nve

rtib

le

flu

ore

scen

t p

rote

ins

(PC

FPs)

Flu

ore

sce

nt

pro

tein

s th

at c

an

"ch

ange

co

lor"

up

on

lase

r

acti

vati

on

Allo

ws

anal

ysis

of

sub

cellu

lar

pro

tein

po

ols

; vi

sau

lizat

ion

pri

or

to

acti

vati

on

; lo

w b

ackg

rou

nd

in p

ost

-

acti

vati

on

ch

ann

el

Blo

cks

two

flu

ore

sce

nt

chan

nel

s;

req

uir

es c

ell

by

cell

acti

vati

on

mEo

s2, K

aed

e,

Den

dra

-2, K

iKG

R, P

S-

CFP

2

revi

ewe

d in

: Lu

kyan

ov

et

al, 2

00

5

Ch

elat

ion

bas

ed t

ags

Sho

rt p

epti

de

tags

th

at h

ave

affi

nit

y to

ch

emic

al s

ub

stan

ces

Size

(6

-12

aa's

)U

nsp

ecif

ic la

bel

ing;

to

xici

tyTC

-tag

, 6H

is-t

ag, P

oly

-

D-t

agre

view

ed

in O

'Har

e e

t al

, 20

07

Po

st t

ran

slat

ion

al

mo

dif

icat

ion

(P

TM)

bas

ed t

ags

Tags

th

at c

an b

e sp

ecif

ical

ly p

ost

-

tran

slat

ion

ally

mo

dif

ied

by

(art

ific

ial)

gro

up

s

Size

(4

-80

aa's

)

Req

uir

es f

ore

ign

en

zym

e to

cat

alyz

e

reac

tio

n; o

nly

po

ssib

le o

n c

ell

surf

ace

AC

P/P

CP

, Bio

tin

,

sulf

atas

e, Q

-tag

revi

ewe

d in

O'H

are

et

al, 2

00

7

Self

lab

elin

g ta

gs

Enzy

mes

th

at c

atal

yze

thei

r

cova

len

t b

ind

ing

to s

mal

l

com

po

un

ds

Allo

ws

mea

sure

men

ts a

t lo

ng

tim

esca

les,

of

larg

e n

um

ber

s o

f ce

lls.

Allo

ws

anal

ysis

of

'old

' vs

'new

'

pro

tein

po

ols

Do

es n

ot

allo

w m

easu

rem

ents

at

sho

rt t

imes

cale

s (s

ec-m

in);

hig

h

flu

ore

sce

nt

bac

kgro

un

d

SNA

P, S

NA

Pf,

CLI

P,

CLI

Pf,

Hal

o, T

MP

Ke

pp

ler

et a

l, 2

00

3 (

SNA

P);

Lo

s an

d

Wo

od

, 20

07

(H

alo

); G

auti

er e

t al

, 20

08

(CLI

P);

Gal

lagh

er e

t al

, 20

09

(TM

P);

Su

n

et a

l, 2

01

1 (

SNA

Pf)

Tim

e S

pec

ific

Tag

fo

r A

ge

Mea

sure

me

nt

of

Pro

tein

s

(Tim

eST

AM

P)

Self

deg

rad

ing

pro

tein

tag

th

at is

inh

ibit

ed b

y d

rug

add

itio

n

Dru

g is

su

ffic

ien

tly

smal

l to

allo

w

acce

ssib

ility

into

tis

sues

of

live

anim

als

On

ly a

llow

s an

alys

is o

f n

ew p

rote

in

po

ols

see

Lin

et

al, 2

00

8Li

n e

t al

, 20

08

Re

com

bin

atio

n In

du

ced

Tag

Exch

ange

(R

ITE)

Flo

xed

pro

tein

tag

th

at is

rep

lace

d

by

a d

iffe

ren

t ta

g u

po

n C

re-

exp

ress

ion

Allo

ws

mea

sure

men

ts o

f b

oth

old

and

new

pro

tein

po

ols

sim

ult

aneo

usl

y

An

alys

is d

epen

ds

on

co

mp

lete

nes

s

of

Cre

-rec

om

bin

atio

n in

all

cells

see

Ver

zijlb

erge

n e

t

al, 2

01

0V

erzi

jlber

gen

et

al, 2

01

0

Au

xin

-in

du

cib

le d

egro

n

syst

em

(A

ID s

yste

m)

Ind

uci

ble

deg

rad

atio

n t

ag, t

hro

ugh

cell-

exo

gen

ou

s p

rote

aso

me

Allo

ws

rap

id s

pec

ific

deg

rad

atio

n o

f

a ta

gged

po

ol o

f p

rote

in

Req

uir

es in

tro

du

ctio

n o

f m

ult

iple

pro

tein

s. O

nly

allo

ws

anal

ysis

of

new

pro

tein

po

ols

see

Nis

him

ura

et

al,

20

09

Nis

him

ura

et

al, 2

00

9

Co

vale

nt

atta

chm

en

t o

f

tags

to

cap

ture

his

ton

es

and

iden

tify

tu

rno

ver

(CA

TC

H-I

T)

Met

abo

lical

lab

elin

g o

f n

ewly

syn

thes

ized

pro

tein

s w

ith

a

met

hio

nin

e an

alo

g

No

req

uir

emen

t fo

r tr

ansg

enes

or

tags

All

pro

tein

s ar

e la

bel

ed

sim

ult

aneo

usl

y, t

hu

s re

qu

irin

g

do

wn

stre

am t

ech

niq

ues

to

pu

rify

pro

tein

s o

f in

tere

st

see

Dea

l et

al, 2

01

0D

eal e

t al

, 20

10

Methods using other kinds of protein tags

or amino-acid analogs

Methods using inducible

fluorescent proteins

Methods using tags that can be

chemically modified

Methods using auto-

fluorescent proteins


75

Principle advantages of using SNAP-tagging include 1) pools of protein

synthesized at different times can be specifically visualized, which allows for

determining the fate of pre-existing versus newly synthesized pools of the

same protein. 2) Because labeling occurs at a population basis, large

numbers of cells can be analyzed in a single experiment. 3) Labeling and

turnover occurs in the culture chamber rather than on the microscope stage.

Therefore, cells are not continuously imaged, but sampled for imaging at any

timepoint from hours to days post labeling. A more extensive comparison of

SNAP with other pulse labeling techniques as well as its advantages and

disadvantages can be found in Table 2.1 and below in the Background

Information.

In this chapter, we explain in detail how to perform a typical SNAP pulse

labeling experiment in human cells. As an example, we will use HeLa cells

that stably express a SNAP-tagged version of CENP-A, a centromere specific

histone variant (Sullivan et al, 1994; Jansen et al, 2007). Using these

CENP-A-SNAP cells, we have been able to show previously that the rate of

centromeric CENP-A turnover corresponds to the rate of cell division, and

thus that CENP-A turns over exclusively by dilution during DNA replication

(Jansen et al, 2007). Using the same technology, we demonstrated that

newly synthesized pools of CENP-A assemble specifically during G1 phase of

the cell cycle (Jansen et al, 2007). The unique dynamics of CENP-A makes

this an excellent illustration of the SNAP-labeling technique. However, this

strategy is easily adaptable to other proteins (e.g. Figure 2.3D) as well, and

similar strategies have been used by us and other investigators, in a range of

organisms and for different applications (Jansen et al., 2007; Erhardt et al.,

2008; McMurray and Thorner, 2008; Maduzia et al., 2010; Bojkowska et al.,

2011; Campos et al., 2011; Dunleavy et al., 2011; Silva et al., in press; also

reviewed in O’Hare et al., 2007).

We will describe two typical types of SNAP-labeling strategies: pulse-

chase (Basic Protocol 1) and quench-chase-pulse (Basic Protocol 2), which

allow for the analysis of old and new protein pools, respectively. We also

Chapter 2

76

describe potential ways to combine SNAP labeling with cell synchronization

and siRNA mediated protein depletion (Basic Protocol 3). Cells can be either

analyzed by live imaging (Basic Protocol 4) or fixed and combined with

standard techniques such as immunofluorescence (Supporting Protocol 2).

In addition, we present an unbiased, automated algorithm that is used for

fluorescence measurements to quantify protein turnover (Basic Protocol 5)

Lastly, we present an evaluation of SNAP pros, cons, pitfalls and ways to

troubleshoot them as well as the recently developed variant of SNAP, SNAPf.


77

BASIC PROTOCOL 1: PULSE-CHASE

This section describes a general method that employs a pulse-chase

strategy for analysis of a specific pool of protein in living cells. By using

fluorescence pulse labeling, the fate and turnover rate of a given protein can

be determined at a particular subcellular location. Specifically, SNAP-tagged

protein that is present at the beginning of an experiment is fluorescently

labeled (pulse) followed by removal of excess dye. After a given amount of

time (chase), cells are analyzed e.g. for localization or quantity of remaining

protein by (quantitative) fluorescence microscopy (Figure 2.2A). An example

of a typical pulse-chase experiment of CENP-A-SNAP is shown in Figure

2.2B. In the approach described here, cells are fixed and analyzed at set time

points following the initial pulse. As a consequence, protein dynamics can be

determined at any time frame (hours, days) post labeling. However, initial

labeling and wash steps require approximately one hour, precluding analysis

of highly dynamic processes that occur at a timescale of seconds to minutes.

Materials

- Cells expressing SNAP-tagged fusion protein (see Supporting Protocol 1)

- Trypsin (cell culture grade, Gibco)

- Standard culture medium abbreviated to “CM” (see Reagents & Solutions).

- TMR-Star (see Reagents & Solutions).

- Sterile DMSO

- Sterile 1X PBS (cell culture grade, Gibco)

- 24-well plates

- Clean, sterile, poly-lysine coated coverslips (12 mm ø; Thickness 1.5)

- Vortex and tabletop centrifuge

Chapter 2

78

Figure 2.2 Pulse-chase imaging. (A) Schematic outlining an in vivo SNAP pulse labeling strategy (Basic Protocol 1).

Cells that produce SNAP-tagged protein are incubated with the SNAP substrate TMR-Star (Pulse) at time T0, rendering

the available cellular pool of SNAP fluorescent. Following substrate washout (Chase), cells continue to synthesize SNAP

protein (light blue) that is not labeled, while the pulse labeled pool turns over. The remaining pulse labeled pool of SNAP

can be visualized and quantified at various time points (Tn) during the chase by microscopy. (B) Example of a pulse-

chase experiment using cells expressing CENP-A-SNAP. CENP-A (top) localizes to centromeres , which are visualized as

subnuclear, diffraction limited foci. Cells are pulse labeled at 0h with TMR-Star after which they are chased and the

remaining pulse labeled pool is visualized by high magnification microscopy at indicated time points. After 72 hours a

small but detectable pool of CENP-A-SNAP is still present at centromeres (inset at 72h shows rescaled

CENP-A::TMR-Star and CENP-C signals). Cells were counterstained with CENP-C (green) and DAPI (blue).


79

Preparation of cells and SNAP-substrates

1) Prepare coverslips in separate wells of a 24-well plate to minimize

the required incubation volumes. Trypsinize cells expressing SNAP-tagged

fusion protein and seed onto the coverslips. Incubate at 37°C, 5% CO2

(henceforth referred to as standard growth conditions). The cell density

depends on a number of factors, mainly cell type and the number of days between

seeding cells and fixation. Ideally, by the time of fixation, the cell density should be

high enough to capture a significant amount of cells on each frame, but not too

high such that cells are fully confluent. Generally 60–80% confluency is ideal. For

HeLa cells (duplication time ~1 day), we aim for having ~5·105 cells at the time of

fixation. E.g., ~1·105 cells are seeded in the afternoon of day 1, if fixation will take

place in the morning of day 4.

2) Dilute TMR-Star stock to 2 μM final concentration in CM. Vortex

briefly to efficiently disperse the DMSO solvent into the aqueous medium.

Dilute an equal volume of DMSO for mock labeling control. Prepare >200 μl

per coverslip. Prepare TMR-Star working stock only as needed and use within the

hour. Although labeling is not yet saturated at this concentration, we use 2 μM to

balance signal intensities and costs per experiment (see Critical Parameters and

Troubleshooting for more details). DMSO addition is an important initial control

to determine background fluorescence unrelated to SNAP-labeling, as well as to

determine the effect of DMSO on the cells. Once these factors have been established

and an effect on cell viability, cell cycle progression, etc. are excluded for a given

cell line, this control can be omitted from subsequent experiments.

3) Spin diluted TMR-Star for 5 minutes at maximum speed (~16.000 g)

in a microcentrifuge to get rid of possible insoluble fluorescent debris.

Recover as much of the supernatant as possible without disturbing the pellet

(may not be visible). Omitting this step will result in occasional but very bright

fluorescent aggregates that interfere with imaging and quantification of

fluorescent signals.

Chapter 2

80

Pulse labeling and washes

4) Aspirate CM from cells and add 200 μl of CM+TMR-Star or

CM+DMSO. Incubate for 15 minutes at standard growth conditions. TMR-

Star treatment of cells will likely result in non-specific fluorescence (see Critical

Parameters and Troubleshooting). It is therefore important to conduct pilot

experiments in which the parent cells without expression of SNAP are labeled to

discriminate SNAP dependent fluorescence from unspecific fluorescence.

5) Wash cells twice with 1 ml sterile PBS (pre-heated to 37°C) to wash

away free substrate. Re-incubate cells in CM under standard growth

conditions for an additional 30 minutes. In our experience, in experiments

where the cells have undergone multiple consecutive treatments prior to labeling

(e.g. synchronization, RNAi, drug treatments), it is preferable to perform the

washes with CM rather than PBS in this and the following steps. This enhances cell

survival.

6) Wash cells twice with 1 ml sterile PBS (pre-heated to 37°C). This

second wash is important to remove any substrate that was retained in the cells

after the initial wash. In our experience, omitting this step leads to a significant

increase in background fluorescence. We calculate the chase period from the

completion of this wash step, as this indicates the last time point during which

SNAP-tagged proteins can be fluorescently labeled.

Chase and post processing

7) There are 3 general options to proceed. Details are presented in

subsequent sections:

a. Pulse-fix: Fix cells immediately after the second wash and either

image directly or process for immunofluorescence (Supporting Protocol

2). This allows testing for SNAP-expression levels and/or serves as a control

for subsequent pulse-chase experiments.

b. Pulse-chase: Re-add 1 ml of CM and incubate cells in standard

growth conditions for a given amount of time (chase period), after which

cells are fixed and treated for immunofluorescence.

c. Pulse-image: Mount cells for live imaging (Basic Protocol 4).


81

BASIC PROTOCOL 2: QUENCH-CHASE-PULSE

In this section we describe a general method that allows for the analysis

of a ‘new’ pool of protein. Specifically, the pool of SNAP-tagged protein that

is present at the onset of an experiment is labeled by a non-fluorescent

SNAP-substrate (quench). Subsequently, after a given amount of time

(chase), cells are labeled with a second, fluorescent substrate (pulse). In this

way only the pool of protein synthesized during the chase period is

fluorescently labeled and hence will be visible by microscopy (Figure 2.3A),

while the initial quenched pool remains undetected (Figure 2.3B). This

approach allows for e.g. quantitative and temporal analysis of protein

translocation and/or assembly into subcellular domains. Examples of typical

quench-chase-pulse experiments are shown in Figure 2.3C–D.

Materials

- All materials used in Basic Protocol 1; in addition:

- BTP (see Reagents & Solutions)

Preparation of cells and SNAP-substrates

1) Prepare coverslips and cells as in step 1 of Basic Protocol 1.

2) Dilute BTP to 2 μM final concentration in CM. Vortex briefly to

efficiently disperse the DMSO solvent into the aqueous medium. Prepare

>200 μl per coverslip. Prepare BTP working stock only as needed and use

within the hour. We have successfully used BTP at concentrations as low as 0.2

μM, resulting in fully quenched SNAP-labeling. However, because full quenching is

essential for accurate interpretation of the results, we prefer using BTP at an

excess of 2 μM (see step 6 for determination of quench efficiency).

Quench labeling and washes

Quench labeling is performed much in the same way as the pulse labeling

described in Basic Protocol 1. The main difference is the time of initial incubation

with BTP: 30 minutes, as compared to 15 minutes for TMR-Star (compare step 3 of

this protocol with step 4 of Basic Protocol 1).

Chapter 2

82


83

Figure 2.3 (previous page) Quench-chase-pulse imaging. (A) Schematic outlining an in vivo SNAP quench-chase-

pulse labeling strategy (Basic Protocol 2). Cells that produce and turnover SNAP-tagged protein are incubated with a

non-fluorescent SNAP substrate BTP (Quench) at time T0, rendering the available cellular pool unavailable for

subsequent fluorescent labeling (dark blue). Following substrate washout (chase), cells continue to synthesize SNAP

protein (light blue) that is not labeled. After a set chase time, nascent protein is specifically labeled with TMR-Star. This

nascent (new) fluorescent pool of SNAP can be visualized and quantified at various time points (Tn) during the

subsequent chase by microscopy. (B) Quench-pulse control. Cells expressing CENP-A-SNAP were either pulse labeled

with TMR-Star (Pulse) or quenched with BTP immediately preceding the pulse labeling step (Quench-pulse) followed by

immunofluorescence and imaging. While pulse labeling results in fluorescent centromeric CENP-A-SNAP, pre-

incubation of cells with BTP (Quench) renders this pool undetectable. Cells are counterstained with anti-HA, which

detects the total pool of (CENP-A-) SNAP. The merged image shows TMR-Star (green) and HA (red) signals together

with DAPI stain (blue). (C) Cells expressing CENP-A-SNAP were subjected to a quench-chase-pulse experiment as

outlined in (A), processed for immunofluorescence and imaged. Nascent CENP-A-SNAP (green) localizes to centromeres

only in a subset of cells (arrow) while remaining non-centromeric in others (arrow heads) highlighting a cell cycle

dependence in nascent CENP-A-SNAP dynamics (Jansen et al., 2007). Cells are counterstained with anti-tubulin (red)

and DAPI (blue) to visualize microtubules and DNA, respectively. (D) Experiment as in (C) except that cells expressing

SNAP-tagged histone H3.1 were subjected to the quench-chase-pulse protocol. H3.1 is a canonical histone that

assembles into chromatin in S phase. Cells that either do not assemble (arrowhead) or are in various stages of nascent

histone H3.1 (red) assembly (arrows) are shown. Cells are counterstained with DAPI to visualize DNA (blue). Panels B

and C are adapted from Jansen et al., 2007.

3) Aspirate CM from cells and add 200 μl of CM+BTP or CM+DMSO.

Incubate for 30 minutes at standard growth conditions.

4) Wash cells twice with 1 ml sterile PBS (pre-heated to 37°C) to wash

away free substrate. Re-incubate cells in CM and standard growth

conditions for an additional 30 minutes. In our experience, in experiments

where the cells have undergone multiple consecutive treatments prior to labeling

(e.g. synchronization, RNAi, drug treatments), it is preferable to perform the

washes with CM rather than PBS in this and the following steps. This enhances cell

survival.

5) Wash cells twice with 1 ml sterile PBS (pre-heated to 37°C). The

second wash is important to remove all traces of free BTP. Omission of this wash

will lead to continued quenching of a proportion of newly synthesized protein

during the chase resulting in smaller pool size of subsequently labeled nascent

protein. We calculate the chase period from the completion of this wash step, as

this indicates the last time point during which SNAP-tagged proteins can be

labeled by the non-fluorescent substrate.

Chapter 2

84

Quench-pulse control

6) Label at least one coverslip with TMR-Star directly following the

quench step (no chase) as described in steps 2 through 7 of Basic Protocol 1.

This is a very important control experiment, as it indicates whether or not the

preexisting SNAP-tagged protein is fully quenched by the available BTP (Figure

2.3B). If this is not the case, results are very difficult, if not impossible, to interpret

correctly. If BTP labeling is not complete, it may be necessary to increase the

concentration of BTP and/or the incubation time. Once conditions that lead to a

complete quenching of SNAP-tagged protein has been determined for a particular

cell type and application, this control can be omitted in subsequent experiments.

Chase

7) Re-incubate cells in CM under standard growth conditions for the

appropriate time. Chase times will dependent, amongst other things, on the

expression levels of the protein of interest and cell type used. Typically in human

cell culture a chase of several hours is required to create a pool size large enough

for subsequent visualization by pulse labeling (e.g. for the case of CENP-A-SNAP,

we found the minimum chase time required to detect nascent protein is 3 hours).


8) For fluorescent pulse labeling and downstream applications, follow

steps 2 through 7 from Basic Protocol 1.


85

BASIC PROTOCOL 3: COMBINING SNAP EXPERIMENTS WITH CELL

SYNCHRONIZATION AND RNAI

Protocol 3.1: Quench-Chase-Pulse

In this section we describe how to combine the SNAP-labeling procedure

with cell synchronization and/or siRNA mediated protein depletion in HeLa

cells. We will give a full overview of multiple synchronization and depletion

steps integrated into a single quench-chase-pulse experiment (Figure 2.4A).

This allows for the determination of the fate of a newly synthesized pool of

protein during the cell cycle and in response to protein depletions. It should

be noted that depending on the specific experiment, in many cases not all

steps will be required. An example of a typical synchronized quench-chase-

pulse experiment is shown in Figure 2.4B.

Materials

- All materials used in Basic Protocol 2; in addition:

- Thymidine, stock of 50 mM in water

- Deoxycytidine, stock of 24 mM in water

- siRNAs and transfection reagents

- Nocodazole stock 5 mg/ml and/or MG132 stock of 10mM

Preparation of cells and synchronization and RNAi

1) Prepare cells on coverslips as described in step 1 of Basic Protocol 1.

2) Perform siRNA transfection for analysis of RNAi mediated protein

depletion at ~48–72 hours post transfection. This step is performed as

described in the product description protocol for Oligofectamine (Invitrogen).

Wait at least 4–5 hours before proceeding to step 3. Protein depletion can only be

performed at this point in the protocol (of a synchronized experiment) if the

depleted proteins are not involved in cell cycle progression. For proteins that are

likely to interfere with S or M phase transition, siRNA transfection is best

performed at a later stage in the protocol (see steps 5 and 9).

Chapter 2

86

Figure 2.4 Combination of SNAP labeling, synchronization, and RNAi. (A) Schematic outline of quench-chase-pulse

protocol combined with double thymidine arrest and RNAi as described in Basic Protocol 3. (B) Combining quench-

chase-pulse labeling with cell synchronization. CENP-A-SNAP cells arrested at the G1/S boundary by double thymidine

block (as in A) were treated with BTP to quench available SNAP pools followed by release into S phase, during which

new protein was synthesized. The nascent pool of SNAP was pulse labeled with TMR-Star after a 7 hour chase (end of S

phase). Cells were fixed at different time points to analyze centromere localization of nascent CENP-A-SNAP in S, G2,

mitosis (M), and G1 phase. While the nascent pool is labeled at 7 hours post release (G2), it does not localize to

centromeres until G1. Cells are counterstained with anti-HA, which detects the total pool of SNAP. (C) Combining

quench-chase-pulse and pulse-chase labeling with RNAi. Asynchronous CENP-A-SNAP expressing cells were

transfected with siRNAs to block synthesis of CENP-A or of a control protein (GAPDH). Cells were pulse-chase (left) or

quench-chase-pulse labeled (right) at indicated time points and assayed 48 hours after siRNA addition to determine the

fate of old and new pools of protein, respectively. CENP-A-SNAP::TMR-Star signals representing old and new protein

pools are shown following RNAi. Cells were counterstained with CENP-C (green) and DAPI (blue). TMR-Star

centromere intensity levels at the centromere were determined by CRaQ (Basic Protocol 5). Average centromeric

CENP-A-SNAP::TMR-Star signals were determined from 3 replicate experiments. Signals after GAPDH RNAi were set

to 1. Error bars indicate standard error of the mean (SEM). While CENP-A RNAi impairs the synthesis and

accumulation of nascent CENP-A (new pool) the pool synthesized prior to siRNA addition is unaffected, demonstrating

the ability to differentially visualize old and new protein pools. Panel B is adapted from Jansen et al., 2007.


87

3) Add thymidine to the CM at a final concentration of 2 mM and

incubate cells at standard growth conditions for 17 hours. Cells that are in S

phase when thymidine is added will arrest immediately, while other cells progress

until they enter S phase and arrest there. Thus, after 17 hours, all cells will be

arrested in S phase albeit at different stages of S phase completion. Spike in

thymidine rather than replacing the CM with CM+thymidine (if RNAi was

performed during step 2), as this would wash out siRNAs from the medium and

reduce the efficiency of protein depletion. If siRNAs are transfected with

oligofectamine in serum free medium in step 2 then serum can be re-added (along

with thymidine) at this point to a final concentration of 10%.

4) Release cells from thymidine arrest by performing two washes with

CM, followed by addition of CM+deoxycytidine (24 μM final concentration).

Incubate cells at standard growth conditions for 9 hours.

5) At 5 hours after release from the first thymidine arrest, siRNA

transfection can be performed for analysis of RNAi mediated protein

depletion at ~24–48 hours post transfection. This step is performed as


Protein depletion can be performed at this point in the protocol for proteins that

are (likely to be) required for mitotic progression, because significant levels of

protein depletion are generally only observed at least 4–5 hours after siRNA

transfection. At this point (~10 hours after release from the first thymidine arrest),

most cells will have passed through mitosis already. For proteins that are not

involved in cell cycle progression, siRNA transfection can be performed at an

earlier point (see step 2), while proteins that are involved in S phase progression

are best depleted at a later point (see step 9).

6) 9 hours after the release described in step 4, add thymidine to the

CM to a final concentration of 2 mM. Incubate cells at standard growth

conditions for 15.5 hours. At this time all cells will have finished DNA

replication, while none have started the next S phase, regardless at which point in

S phase they were arrested initially. Spike in thymidine rather than replacing the

CM with CM+thymidine (if RNAi was performed during step 5), as this would

wash out siRNAs from the medium and reduce the efficiency of protein depletion.

Chapter 2

88

If siRNAs are transfected with oligofectamine in serum free medium in step 5 then

serum can be re-added (along with thymidine) at this point to a final

concentration of 10%.

Quench labeling and washes

7) 15.5 hours after thymidine addition in step 6, perform quench-

labeling (and 1st washout thereof) essentially as described in steps 3-6 of

Basic Protocol 2, except that 2 mM thymidine is added to the CM+BTP and

CM in order to maintain cells in the S phase arrest until after the labeling is

complete.

8) 30 minutes after step 7, release cells from second thymidine arrest

and perform second BTP washout by performing two washes with CM,

followed by addition of CM+deoxycytidine (24 μM final concentration). This

step combines the second wash of the BTP-labeling and release from second

thymidine arrest. Cells will now (16 hours after initiation of second thymidine

arrest) all be synchronously released from early S phase and will progress

through the cell cycle largely synchronous for approximately one full cell cycle.

Cells will enter mitosis at ~9–11 hours after release from the second thymidine

arrest.

Chase

9) ~3 hours after release from the second thymidine arrest (step 8),

siRNA transfection can be performed for analysis of RNAi mediated protein

depletion at early timepoints post transfection. This step is performed as


Protein depletion can be performed at this point in the protocol for proteins that

are (likely to be) required for S phase progression, because significant levels of

protein depletion are generally only observed at least 4–5 hours after siRNA

transfection. At this point (~8 hours after release from the second thymidine

arrest), most cells will have passed through S phase already. Since maximum

protein depletion is generally observed 24–48 hours post-transfection, for proteins

that are not involved in S phase progression, siRNA transfection are best

performed at an earlier point (see steps 2 and 5).


89


10) TMR-Star pulse labeling and downstream applications are

performed as described in Basic Protocol 1, steps 4–7 at different time

points following BTP-quench and thymidine release depending on the

application. If siRNAs are transfected with oligofectamine in serum free medium

in step 9 then serum can be re-added after 2nd washout of TMR-Star.

11) Optional: To gain higher synchrony in and around mitosis, cells can

be arrested in mitosis by addition of the microtubule depolymerizing drug

nocodazole to 250 ng/ml final concentration will result in a prometaphase

arrest), or addition of nocodazole and washout of this drug into the

proteasome inhibitor MG132 (24 μM final; metaphase arrest). Nocodazole

can be added at any time to allow accumulation of cells in mitosis (optimal

concentration will depend on cell type). MG132 will arrest cells in interphase

unless added in late G2 phase in which case cells will continue to cycle until

metaphase. Metaphase synchronization of cells by MG132 is therefore best

combined with a (double thymidine arrest, release and) nocodazole arrest and

release. Arrest from these drugs is reversible, allowing the analysis of cells that are

synchronously released from mitosis.

12) Optional: 9 hours after release from the second thymidine arrest,

thymidine (final concentration of 2 mM) can be re-added to collect cells

synchronously at the next G1/S phase transition, 15 hours later.

Protocol 3.2: Pulse-Chase

Here, we describe a different version of Basic Protocol 3, where a pulse-

chase strategy is employed rather than quench-chase-pulse. This allows for

tracking of a pre-existing pool of SNAP (as opposed to a newly synthesized

pool) in relation to the cell cycle and in response to protein depletions. This

protocol is highly similar to the Basic Protocol above and therefore we will

only describe the key steps that are different between the two protocols.

Chapter 2

90

This alternate protocol can also be performed in parallel with Protocol

3.1, e.g. to distinguish a differential effect on separate pools of the same

protein (an example is given in Figure 2.4C).

Materials

- All reagents used in Protocol 3.1, except for BTP

Preparation of cells and synchronization and RNAi

1) Cells are prepared, and treated with siRNAs and synchronized with

thymidine as described in Protocol 3.1 steps 1–6.


2) 15h and 15 minutes after thymidine addition in step 6 of Protocol 3.1,

perform TMR-Star pulse labeling (and 1st washout thereof), essentially as

described in steps 4–6 of Basic Protocol 1, except that 2 mM thymidine is

added to the CM+TMR-Star and CM in order to maintain cells in the S

phase arrest until after the labeling is complete.

3) 30 minutes after step 2, release cells from second thymidine arrest

and perform second TMR-Star washout by performing two washes with CM,

followed by addition of CM+deoxycytidine (24 μM final concentration). This

step combines the second wash of the TMR-Star-labeling and release from second

thymidine arrest.

4) Proceed to downstream applications as described in step 7 of Basic

Protocol 1.


91

BASIC PROTOCOL 4: LIVE IMAGING OF PULSE LABELED CELLS

This section will describe the basic procedure and considerations of

imaging SNAP substrate signals in living cells. Live cell imaging of SNAP

labeled proteins differs from conventional imaging of autofluorescent

proteins (e.g. GFP) in that SNAP substrates generate considerable

background staining, particularly in membrane compartments. This

requires specific signals to be of sufficient strength to maintain an adequate

signal-to-noise ratio. Despite this constraint, live cell imaging of temporally

labeled SNAP-tagged proteins is a powerful approach to determine the fate

of protein pools of different ages (Figure 2.5). We will discuss two different

methods (Protocols 4.1 and 4.2) of preparing cells for live imaging.

Figure 2.5 Live cell imaging of SNAP labeled cells. Schematic outlines cell synchronization and quench-chase-pulse

labeling steps as shown in Figure 2.4B. Following pulse labeling, cells are cycled into mitosis and mounted for live cell

imaging (Basic Protocol 4). Time lapse series is shown of a cell in mitosis. At early time points, TMR-Star signals are

non-centromeric, but are observed near the cell periphery, probably reflecting non-specific retention of the fluorescent

substrate in cellular membranes. As cells exit from mitosis (after anaphase, t=0 minutes) TMR-Star signal accumulates

at centromeres from t=50 minutes onwards. Cells express GFP-CENP-C that constitutively labels centromeres

throughout the experiment. Insets show colocalization of nascent CENP-A-SNAP::TMR-Star (green) with centromeres

(CENP-C, red). Image is adapted from Jansen et al., 2007.

Chapter 2

92

Materials

- Materials and reagents for SNAP pulse labeling as described in Basic

Protocol 2; in addition:

- Live imaging medium, referred to as “LM” (see Reagents & Solutions)

- Microscopy facilities suitable for live cell imaging (see below for some

general considerations)

- VALAP (see Reagents and Solutions; for Method 1 only)

- Oxyrase (Oxyrase Inc.), stock of 30 U/ml (for Method 1 only)

- 6-well plates(for Method 1 only)

- 22x22 mm square coverslips (for Method 1 only)

- Permanent double-sided tape (Scotch; for Method 1 only)

- Standard glass slides (for Method 1 only)

- 8-well Chambered Coverglass (Lab-Tek; for Method 2 only)

- Mineral oil (for Method 2 only)

Protocol 4.1: double side sticky tape chamber

This method is adapted from (Waterman-Storer & Salmon, 1997).

Preparation of cells and pulse labeling

1) Grow cells expressing SNAP-tag fusion proteins in 6-well plates onto

22x22 mm square glass coverslips in 2 ml of culture medium to 60–80%

confluency.

2) Perform quench and pulse labeling steps as in Basic Protocols 1 or 2,

except that labeling volumes of 600 μl are used in 6-well plates.

Mounting of live cell chambers

3) Glue 3 layers of double-sided tape, cut to ~3 mm wide, along the two

long edges of the glass slide such that when a coverslip is placed on top, it is

sealed on two sides (along the longitudinal end of the glass slide).


93

4) Mount coverslips, cells facing down, onto the glass slide prepared in

step 3.

5) Slowly, flow in LM under the coverslip, until the chamber is filled by

capillary action (<1 ml). Perform this step as quickly as possible after step 4 to

avoid cells drying out. Phenol red is omitted from the LM to avoid background

fluorescence. The use of CO2 independent medium (e.g. buffered by HEPES) is

required to maintain pH in this chamber type as it is sealed from outside air

contact. Optionally, 0.5 U/ml Oxyrase is included in the medium. Oxyrase is an

oxygen-scavenging enzyme that helps reduce photobleaching and phototoxicity

due to reactive oxygen species.

6) Seal the chamber on all sides with VALAP and image live cells on the

microscope.

Protocol 4.2: 8-well coverglass slides

Preparation of cells and pulse labeling

1) Grow cells expressing SNAP-tag fusion proteins directly in an 8-well

chambered coverglass slides to 60–80% confluency.

2) Perform quench and pulse labeling steps as in Basic Protocols 1 or 2,

except that labeling volumes of 100 μl are used in 8-well chambered

coverglass slides.

Mounting of live cell slides

3) Following labeling and washes, replace medium with LM to a final

volume of 300 µl. Seal wells with 100 µl mineral oil. Due to small sample

volumes it is critical to prevent evaporation of medium during the time lapse.

Sealing of the medium-air interface with mineral oil is an effective method to

achieve this. The use of mineral oil is compatible with the use of DIC optics during

live cell imaging.

Chapter 2

94

General considerations regarding the microscope setup.

A detailed description of microscope parameters is outside the scope of

this unit. Typically, for live cell imaging of mammalian cells, a heated

chamber is required to maintain both the cells and the microscope stage at

the appropriate temperature. SNAP-dyes can be imaged in principle with

any microscope setup as long as appropriate laser lines or filters are used. A

variety of fluorescent SNAP-substrates is available from New England

Biolabs and others can be found in the existing literature (e.g. Keppler et al,

2004, 2006). See also Critical Parameters and Troubleshooting below.

Fluorescent SNAP substrates are based on organic dyes (e.g. TMR).

Bleaching is therefore not as big a concern as with autofluorescent proteins

such as GFP or RFP. However, due to non-specific labeling (of membranes),

background signals are relatively high as compared to autofluorescent

proteins. Exposure times, laser strength, neutral density filter settings, and

choice of temporal resolution largely depend on signal strength and

considerations of cellular phototoxicity.


95

BASIC PROTOCOL 5: AUTOMATED QUANTIFICATION OF SNAP-

TAGGED PROTEIN TURNOVER AT CENTROMERES

In this section we will present a method to perform unbiased

fluorescence quantification of diffraction limited spots. We present here a

case for centromeres, but this approach applies to any point source signals

in living or fixed cells. To this end, we developed an automated algorithm

which we name CRaQ (Centromere Recognition and Quantification). This

ImageJ based macro detects spots in one channel and subsequently

measures the fluorescence intensities in another. This allows for accurate

detection and quantification of thousands of spots in a fast, unbiased, and

effortless way.

In brief, centromeres are recognized and the centroid position is

determined. Next, fluorescent intensities are measured for each centromere

by placing a small box around the centroid position of the centromere. The

peak intensity value within the box is then corrected for local background by

subtraction of the minimum pixel value. We have evaluated the accuracy of

CRaQ by re-analyzing previously published quantifications that were

performed by manually selecting spots (in a reference channel) by eye

(Jansen et al, 2007). The results that are obtained by CRaQ are practically

identical to the previously published results (Figure 2.6F). In addition, we

evaluated the robustness of CRaQ by analyzing replicates samples (because

CRaQ is a deterministic algorithm, re-analyzing identical datasets without

changing parameters will lead to identical results). We show that

quantification of replicate samples by CRaQ leads to a standard error of the

mean (SEM) of ~5%, which is likely attributable to biological and/or

experimental variation (Figure 2.6G). Thus, CRaQ allows for accurate and

reproducible measurement of centromere specific signals.

Chapter 2

96

Figure 2.6 Centromere Recognition and Quantification (CRaQ). (A–E) Overview of automated steps taken by CRaQ

(Basic Protocol 5). (A) DAPI images are thresholded and converted to binary masks. (B) REFERENCE images are

filtered and (C) overlaid with the mask to produce a masked reference. (D) This image is again thresholded and spots

that fit with the given parameter settings are exported as regions of interest, which are overlaid and measured in the

DATA images (E). A blowup is displayed to show the accuracy and frequency of centromere recognition. Note that raw

images are in capitals, while processed images are in lowercase letters throughout. (F) CRaQ was used to re-analyze

manually selected and quantified centromeres in Jansen et al., 2007. The two methods lead to practically identical

results, thus cross-validating each other. (G) Replicate samples were analyzed by CRaQ and standard error of mean

(SEM) is plotted as a percentage of the average for four independent experiments, each consisting of four replicates.


97

Because this protocol is performed in an automated fashion, in this

section we will first describe the steps that the researcher must take

(preparation of the data, CRaQ initiation and parameter settings, etc). Next,

we will give an overview of the actual steps that the algorithm goes through

for each image (Figure 2.6A–E). This provides users with a good idea of how

automated recognition and quantification is performed.

Materials

- A standard computer

- ImageJ software, including the “Grouped_ZProjector” plugin (both freely

available from NIH, http://rsbweb.nih.gov/ij/index.html)

- CRaQ plugin for ImageJ (freely available from

http://uic.igc.gulbenkian.pt/micro-macros.htm)

- Digital images of SNAP-labeled cells, as described in Basic Protocol 1 or 2

after fixation and antibody staining as described in Supporting Protocol 2

Input data preparation (before running CRaQ)

1) Input files should consist of all of the channels of a single frame in

one file. CRaQ can use either stacks or projected images as an input. The

order of images in a file should be such that the entire image sequence of

one channel is followed by the image sequence of the second channel, etc.

This as opposed to having all channels for one frame followed by the all the

channels for the next frame. Additional channels that are not used during the

quantification process can be stored in the same files and will be ignored by CRaQ.

2) Note the order in which the data, reference and DAPI channels are

stored in the input files. In principle, only a data channel (the channel that will

be quantified) is essential for CRaQ to run. See Critical Parameters and

Troubleshooting for reasons and tips for using an independent reference channel.

3) Ideally, the order in which the images should be taken is 1st data, 2nd

reference, 3rd DAPI, and any additional channels subsequently. In this way,

potential bleaching of the data signal during reference or DAPI channel

acquisition will occur only after the data have been collected.

Chapter 2

98

4) Create a “base folder” with separate subfolders that contain all the

images for each condition (e.g. RNAi, replicates, cell types, cell cycle stages,

etc). Any images that are located directly in the base folder will not be detected by

CRaQ. If all images are to be quantified separately, they can be put into a single

subfolder, as the output data file indicates which data points are derived from

which image. Only files with extension “.dv” (produced by SoftWorx, Applied

Precision) or “.tif” will be recognized by the macro. Thus additional files (log files,

etc.) can remain in the base folder without interfering with the macro. When

rerunning CRaQ on a previously analyzed data set (e.g. using different settings),

make sure to copy the previous data output prior to rerunning, as all files will be

overwritten.

Installing and Running CraQ:

5) Copy the CRaQ plugin into your “…/ImageJ/plugins/Analyze” folder

and restart ImageJ. Run the algorithm by selecting it from the

Plugins>Analyze menu inside ImageJ.

6) In the window that appears you can set the order in which the Data,

Reference, and DAPI channels are stored in the input files, as well as the

total number of channels. In addition, you can choose to change the

standard parameter settings of CRaQ.

Setting the Parameters:

The default parameters are those that we have found to work best for

most purposes. However, depending on particular experiments, this will not

always be the case. What follows is an explanation of each parameter and

how and why to change them.

Square size. The size of the box placed around each centromere. Square size 7

means a box of 7x7 pixels. This will generally not change the results much, as only

the maximum and minimum pixel values in each box are used. However, make

sure that the box is big enough to contain some background pixels, but not too

large, as this will make the background signal “less local” and will decrease the

number of spots identified due to exclusion of overlapping boxes.


99

Minimum circularity. This measure helps to exclude clustered centromeres.

Circularity is a measure of how much the recognized spots resemble a circle, where

1 is a perfect circle and 0 a straight line (the most imperfect circle). Since

centromeres appear as diffraction limited spots, they should theoretically be

perfectly circular and this measure can be set very close to 1 (most single

centromeres actually have a circularity of 1). Because brighter centromeres tend to

be less circular, decreasing circularity will allow you to pick up more bright

centromeres, but will also increase the chance of picking up doublets, clusters or

non-centromeric regions.

Max feret’s diameter. This measure is also made to exclude doublets/clusters

and is required because occasionally clusters have a very high circularity. The

feret’s diameter is the longest diameter of a spot. Together, stringent circularity

and feret parameters are able to exclude most doublets. Increasing the maximum

feret’s diameter has a similar effect to decreasing minimum circularity and vice

versa.

Min/max centromere size. The minimum and maximum size a centromere

can have (in total number of pixels). Basically having a larger maximum size can

include both brighter centromeres and more doublets. Again, a lower max

centromere size will exclude the last few doublets, but may also exclude some of the

brightest (in the reference channel) single centromeres. Increasing the minimum

will discard more false positive spots, but also more truly positive (dim) spots.

Threshold offset. This parameter sets the sensitivity of recognition of spots in

the thresholded image. Increasing the offset makes the threshold more sensitive to

lower signals. This will both increase the number of dim spots (true & false

positives), and decrease the number of bright centromeres (false negatives), as

these will now appear bigger and potentially less circular.

Chromatic aberration correction. If there is a constant chromatic aberration

between reference and data channels, this can be corrected by CRaQ. If the

reference channel has spots shifted towards the top/right, then input positive

numbers. If the reference channel has spots more to the bottom/left, input negative

numbers.

Chapter 2

100

Data output:

All output files will be produced in an output folder inside the base

folder. These are the different output files that will be produced by CRaQ:

A single file entitled: “logfile.txt”. This file contains the base directory and

parameter settings used. Keep this file or copy info for further reference, replicate

experiments or comparison between experiments and parameter settings.

One “*.txt” file for each condition (i.e. subfolder of the base folder). These

files contain the actual measurements made by CRaQ with a reference to the

corresponding image and centromere spot. These can be directly copied to

analysis software such as Excel (Microsoft) or Prism (Graphpad) for further data

processing and analysis.

One “*.zip” file for each image. This contains all the recognized spots for that

image as ROI lists for ImageJ. To view spots, open the image and the

corresponding *.zip file in ImageJ. A “ROI Manager” window will appear, and you

can either see all spots by selecting “Show all” or select and display any individual

spot.

If stacks where used as input images, a projection of each image is saved.

All channels of an image will be saved together in a single *.tif file.

How it works:

1) Convert DAPI to mask (Figure 2.6A). This mask will exclude any spots

that are recognized but do not overlap with DNA.

2) Signal enhancing on reference (Figure 2.6B). This allows for more

accurate spot recognition.

3) Overlay the mask and the reference (Figure 2.6C). This excludes any

non-DAPI signals.

4) Spots that are significantly above background and fall within the

restrictions given by the parameter settings are detected and exported as

ROI (region of interest) lists (Figure 2.6D). Note that generally <50% of all

centromeres are found. However, the recognition of centromeres does not seem to

depend on the brightness of centromeres in the reference channel, much the less in


101

the data channel. Exclusion of centromeres occurs mostly based on too close

proximity to other centromeres. Even though many centromeres are excluded,

these measurements will always be orders of magnitude faster and less biased

than doing the same by hand.

5) Measure the centromere spots in the data channel (Figure 2.6E). A

box of a set size is placed around the center of mass of a ROI. In these boxes, the

maximum and minimum values of the Data channel will be measured. The

minimum is subtracted from the maximum and that is represented in output. In

addition, these boxes are also saved as output. Note that no transformations or

background subtractions, etc are made to the Data file before measuring. This

means that you are actually measuring raw data. Alterations are only made (but

not saved) in the other channels, and are used to efficiently localize centromeres.

To exclude overlapping boxes, thus measuring the same spot twice, each box is

made black after being measured (value = 0). The macro is programmed to

exclude any box containing pixels of value 0. These black boxes are not saved to the

data file, so that raw data is preserved. If there is a chromatic aberration, this can

be set in the parameters (see above) and boxes are shifted accordingly before

measuring. The saved output boxes are the ones that correspond to the reference

channel.

Chapter 2

102

SUPPORTING PROTOCOLS

Supporting Protocol 1: Expression of SNAP-fusion proteins

We use SNAP source vectors that include a triple HA tag for efficient

detection of SNAP-tagged proteins by immunoblotting or

immunofluorescence. Maps of SNAP-3XHA, 3XHA-SNAP and 3XHA-SNAPf

constructs are in Appendix. Fusion proteins are subsequently subcloned in

transient expression vectors or in retroviral constructs (pBABE, see below)

for stable expression.

For piloting SNAP fusion performance in living cells, we use standard

transient transfection methods for obtaining SNAP protein expression. We

transfect cells using liposome based methods [e.g. Lipofectamine

(Invitrogen) or Fugene (Roche) according to manufacturer’s instructions]

and assay protein expression and SNAP activity 48 hours after transfection.

For comprehensive experiments, we typically use monoclonal cell lines

stably expressing SNAP fusions obtained by retroviral mediated

transduction and selection. We use recombinant Moloney murine leukemia

(Mo MuLV) retroviral particles for the delivery of SNAP-tagged transgenes

into host cell lines (e.g. HeLa or hTERT-RPE). This system is derived from a

set of pBABE retroviral vectors (Morgenstern and Land, 1990). Virus

particles are assembled in HEK293-GP cells that express the essential Mo

MuLV gag and pol genes along with transient delivery of the vesicular

stomatitis virus G protein (VSV-G) that results in a pantropic virus with a

broad host cell range (Burns et al, 1993; Yee et al, 1994).

Materials

- HEK 293-GP cells (Burns et al., 1993)

- Trypsin (Cell culture grade, Gibco)

- Standard culture medium abbreviated to “CM” (see Reagents & Solutions)

- Lipofectamine LTX (Invitrogen) and associated products

- Sterile PBS (Cell culture grade)


103

- Polybrene (hexadimethrine bromide, Sigma), stock at 8 mg/ml

- Selection drugs (e.g. Blasticidin S, puromycin, or hygromycin)

- Bovine serum albumin (BSA)

- 10 cm standard cell culture dishes; 10 ml syringes; 0.45 μm filters; 6- and

96-well plates

- Single cell sorting equipment

Production of viral particles using pBABE based retrovirus

1) Trypsinize and seed one million HEK293-GP cells in a 10 cm dish

and culture in CM using standard growth conditions.

2) After 24 hours cells are transfected with 5 μg pBABE + 2 μg pVSV-G

using 17.5 μl lipofectamine LTX (Invitrogen), according to manufacturer’s

instructions.

3) Incubate cells using standard growth conditions and replace medium

with serum containing medium after 4 hours or overnight incubation.

4) Incubate cells for 3 days for viral particle production.

5) Harvest the medium directly from the cells and filter through a 0.45

μm filter using a 10 ml syringe to avoid cellular contaminants.

6) Aliquot (1 ml) and freeze viral stocks at -80°C in or use directly for

infections.

Infection of target cells

7) Trypsinize and seed target cells into 2 wells of a 6-well plate, such

that cells are at 30–40% confluence at time of infection.

8) Add 8 μg/ml polybrene immediately prior to virus addition.

9) Add 250 μl viral stock from step 6) to one well and 750 μl to the

second well. Add CM to a final volume of 1 ml.

10) After 24 hours of infection, replace medium with CM.

11) Let cells proliferate until they reach confluency (at least 24 hours

later).

Chapter 2

104

12) Trypsinize cells, combine the 2 wells, and plate in a 10 cm dish

containing the appropriate drug selection. We use pBABE vectors with

Blasticidine S (Blast), puromycin or hygromycin resistance cassettes. E.g. HeLa

cell clones are drug selected with 5 μg/ml Blast, 5 μg/ml puromycin, or 250 μg/ml

hygromycin.

13) Select cells until colonies are visible by the naked eye (10–20 days).

14) Trypsinize and pool the clones and amplify for single cell sorting.

15) To isolate monoclonal lines, cells are washed in sterile PBS,

resuspended in sterile PBS + 5% BSA and sorted by standard flow sorting

(using scatter to identify single cells) into 96-well plates containing

conditioned culture medium (see Reagents & Solutions).

Supporting Protocol 2: Cell fixation and immuno-fluorescence

In this section we describe a general method for fixation (of SNAP pulse

labeled cells), immunofluorescence detection and DAPI staining.

Immunofluorescence for detection of proteins unrelated to SNAP but

localized at the same subcellular location allows for an independent measure

to be used in image quantification using CraQ (see Basic Protocol 5, and

Commentary). Please note that many other equally effective protocols for

this purpose exist. As this is a general protocol we do not comment on

specific antibody conditions and concentrations as this will need to be

determined for each specific application.

Materials

- 1X PBS

- 4% Paraformaldehyde in 1X PBS, referred to as “PFA”

- 0.1 M Tris-HCl, pH 7.5

- PBS-TX (1X PBS + 0.1% Triton X-100)

- DAPI solution (see Reagents & Solutions)

- MOWIOL (see Reagents & Solutions)


105

- Nail polish

- Humid dark box: Can be made from an empty micropipette tip-box filled with a

small layer of water, a thick sponge covered by a glass plate. Any transparent

surface of the box is covered with aluminum foil

- Parafilm

- Clean, sterile, poly-lysine coated coverslips (12 mm ø; Thickness 1.5)

- Fine forceps with sharp pointed ends

- IF blocking buffer (see Reagents & Solutions)

- Standard glass slides

Cell fixation

1) Grow and SNAP pulse label cells on glass coverslips in 24-well plates

as described in Basic Protocols 1–3.

2) Wash cells twice in 1 ml PBS, pre-heated to 37°C.

3) Fix cells for exactly 10 minutes at room temperature in 500 μl PFA,

pre-heated to 37°C.

4) Aspirate PFA and quench by adding 1 ml of 0.1 M Tris, pH 7.5 for 5

minutes. Cells can be stored at this point for up to a few days in PBS at 4°C, or up

to 1 month in PBS + 0.04% NaN3 at 4°C.

Antibody detection

5) Permeabilize cells by washing twice in 1 ml of PBS-TX for 5 minutes.

6) Carefully lift coverslips with a forceps and move to a parafilm

covered glass plate in humid dark box. Humid dark boxes prevent coverslips

from drying and fluorescent dyes from photo-bleaching. Parafilm is a convenient

receptacle for coverslips as its hydrophobic surface allows the application of small

volumes to the coverslips without spilling over to neighboring coverslips.

7) Block cells for 30 minutes, 37°C in blocking buffer. Use 75 μl per

coverslip.

8) Incubate cells with primary antibody diluted in blocking buffer for

60 minutes, 37°C. Use 30 μl per coverslip.

Chapter 2

106

9) Wash coverslips in 75 μl PBS-TX 3 times for 5 minutes at room

temperature.

10) Incubate secondary fluorescent antibody diluted in blocking buffer

for 45 minutes, 37°C. Use 30 μl per coverslip. Centrifuge diluted fluorescent

antibodies for 5 minutes at maximum speed (~16.000 g) to deplete any fluorescent

aggregates that may interfere with fluorescent imaging. Use supernatant for

staining.

11) Wash coverslips in 75 μl PBS-TX 3 times for 5 minutes at room

temperature.

12) Incubate cells in 50 μl DAPI (500 ng/ml final concentration) for 5

minutes at room temperature.

13) Replace DAPI solution with PBS.

14) Carefully pick up coverslips with a forceps, remove excess liquid by

aspiration and/or filter paper, and mount on a glass slide (cells facing down)

in ~5 μl Mowiol. Allow the Mowiol to solidify overnight at 4°C in the dark.

15) Seal coverslips using nail polish to avoid air contact during the

imaging process.

Reagents & Solutions

BTP (bromothenylpteridine): A 2 mM stock is prepared by dissolving 100

nmol lyophilized SNAP-Cell Block (New England Biolabs, cat# S916S) in 50 μl

DMSO (sterile). Shake for 10 minutes in an eppendorf shaker at maximum speed to

dissolve. Store for 1 month at -20°C or aliquot and store at -80°C.

Conditioned culture medium (for HeLa): 50% fresh CM + 50% CM

harvested from HeLa cultures in log growth phase, 0.45 μM filtered.

DAPI(4',6-Diamidino-2-phenylindole dihydrochloride): A 1 mg/ml stock is

prepared in water. Store at -20°C. Dilute 2000 fold in PBS for working solution.

IF blocking buffer: 2% fetal bovine serum, 2% BSA, 0.1% Triton X-100, 0.04%

NaN3, in 1X PBS.


107

Live imaging medium: phenol red-free, CO2-independent medium (e.g. DME

or Leibovitz’s L-15) supplemented with 10% fetal bovine serum, 2 mM Glutamine

(all from Gibco).

MOWIOL: Ingredients: Mowiol 4-88 (Calbiochem), Glycerol, DABCO (1,4-

diazabicyclo[2.2.2]octane, Sigma).

1) Mix Mowiol 4-88 and glycerol in a 2:5 ratio (w/w).

2) Add 0.714 ml water/gram of Mowiol/glycerol mixture and stir overnight at

room temperature.

3) Add 2 volumes of 0.2 M Tris (pH 8.5) for each volume of water added and heat

at 50°C for 10 minutes with occasional mixing.

4) Centrifuge at 5.000 g for 15 minutes and remove debris.

5) Add DABCO to 2.4% and mix slowly.

6) Centrifuge at 5.000 g for 15 minutes and remove debris.

7) Aliquot and store at -20°C.

Standard culture medium (for HeLa and HEK293-GP): DMEM + 10% NCS

(newborn calf serum), 100 U/ml penicillin, 100 µg of streptomycin, 2 mM

Glutamine (all from Gibco). Other cell types may require different growth media.

TMR-Star: A 200 μM stock is prepared by dissolving 30 nmol lyophilized

SNAP-Cell TMR-Star (New England Biolabs, cat # S9105S) in 150 μl DMSO

(sterile). Shake for 10 minutes in an eppendorf shaker at maximum speed to

dissolve. Store for 1 month at -20°C or aliquot and store at -80°C.

VALAP: Vaseline:lanolin:paraffin 1:1:1 (w/w).

1) Heat paraffin to 50°C in a large beaker in a water bath.

2) When paraffin is melted mix in vaseline and lanolin.

3) Stir to mix and aliquot, store at 4°C.

4) Heat to 50°C prior to use

Chapter 2

108

BACKGROUND INFORMATION

Historical background

The SNAP-tag is a modified version of human O6-alkylguanine-DNA

alkyltransferase (hAGT). Endogenous hAGT is a DNA repair enzyme that

removes a broad range of alkyl adducts from the O6 position of guanines in

DNA. It acts as a suicide enzyme that catalyzes a covalent binding reaction

between itself and the alkyl group that is removed from guanines, thereby

restoring DNA integrity but inactivating its own catalytic activity (Pegg,

2000). SNAP, the modified form of hATG, has lost its affinity to DNA but

efficiently reacts with soluble O6-benzylguanine (BG), of which the benzyl

moiety is readily transferred to the SNAP protein (Figure 2.1; Juillerat et al,

2003; Keppler et al, 2003). The benzyl rings in BG can be coupled to a large

variety of molecules (Keppler et al., 2003, 2004, 2006) that include

fluorescent moieties as well as non-fluorescent ones (a selection of SNAP

substrates is presented in Table 2.2).

General considerations for SNAP-based protein turnover assays

A number of techniques exist to analyze protein turnover (Table 2.1). A

common approach to in vivo protein turnover is the use of fluorescence

recovery after photobleaching (FRAP). In this method, autofluorescent

proteins are fused to proteins of interest that localize to a specific subcellular

location. Local irreversible bleaching followed by repopulation of a bleached

area by unbleached molecules from neighboring regions provides

information of the local rate of protein turnover (Lippincott-Schwartz et al.,

2001; and references therein). A reciprocal technique utilizes inducible

fluorescent proteins, which can be activated by a focused laser, which allows

tracking of a specific pool of photo-activated protein (Lukyanov et al., 2005;

and references therein). While widely applied, FRAP and photo-activation

experiments suffer from three specific drawbacks. 1) Measurement of

fluorescence recovery or photoactivation typically requires continued

imaging of cells, leading to problems such as photobleaching and


109

phototoxicity, thereby restricting the time in which turnover can be

measured to a few hours at most. This precludes measurement of long-term

turnover rates. 2) A focused laser is required to bleach or activate

fluorescence preventing the analysis of large numbers of cells

simultaneously. Lastly 3), the turnover rates using FRAP and photo-

activation are a product of the “on” and “off” rates of a protein which cannot

be assessed separately. SNAP-based pulse labeling differs from traditional

FRAP experiments in that a fluorescent pool is created by pulse labeling

with the addition of an external dye to the culture medium. Therefore, first

and foremost, imaging and quantification of its fluorescence can commence

at any time following labeling (hours, days after pulse labeling). This allows

analysis of protein turnover at very long time scales. Secondly, because the

entire cell population is treated with the dye in bulk, large numbers of cells

are available for simultaneous imaging and analysis. Lastly, the combination

of serial dark and fluorescent pulse labeling strategies (“pulse-chase” and

“quench-chase-pulse”) allows for the separate determination of turnover of

pre-existing pools (off-rates) and turnover of newly synthesized pools of

protein (on-rates) (Figure 2.2 and 2.3).

Several other methods capitalize on similar advantages such as other

self-labeling or destructive enzymes (see Table 2.1). We would like to

highlight one recently developed method named “Recombination Induced

Tag Exchange” (RITE), which allows for similar applications as SNAP-

tagging while using a fundamentally different strategy (Verzijlbergen et al.,

2010). It uses recombination induced switching of expression of

differentially tagged versions of the same gene. This allows for the

simultaneous visualization, tracking, and/or analysis of the original (pre-

switched) pool as well as a nascent one (Radman-Livaja et al., 2011).

However, this method relies on tight control over induction of Cre-mediated

recombination which is difficult to achieve in some systems (most metazoan

cell lines).

Chapter 2

110

The advantage of assessing long-term dynamics also implies a major

disadvantage of SNAP-based pulse labeling. Labeling and washing steps

require approximately 1 hour rendering this method inappropriate to assess

protein dynamics at short timescales (seconds to minutes), as pulse labeled

proteins will have reached their steady state equilibrium before imaging can

determine their dynamics. However, improvements are currently being

made to both the SNAP-enzyme and the fluorescent substrates thereof,

which would in principle allow labeling steps of 5 minutes without the need

for any washes (see below and Sun et al., 2011).

Critical Parameters and Troubleshooting

SNAP labeling: Choice of substrate

One very important parameter during the pulse-chase and quench-

chase-pulse procedure in living cells is the choice of SNAP-substrate used.

The limiting characteristic seems to be the ability of substrates to efficiently

pass the cell membrane, as many substrates tend to strongly label the cell

membrane while barely labeling intracellular SNAP proteins. In our

experience, non-fluorescent benzylguanine (BG) or bromothenylpteridine

(BTP) enter cells efficiently. However, addition of (bulky) side groups may

impede the cell permeability.

Thus, although there is a large variety of fluorescent substrates for intra-

cellular labeling, the efficiency at which these enter the cells is not always

the same. For this reason, using the optimal fluorophore for the particular

microscopy and filter setup used has to be balanced with the cell

permeability of this substrate. We generally obtain the best results with

SNAP-Cell TMR-Star (New England Biolabs).

It is for this reason that we prefer to use BTP for quench steps in the

quench-chase-pulse procedures rather than using multiple different

fluorescent substrates (see Basic Protocol 2), because complete labeling of

the initial pool is essential to ensure visualization of the subsequent newly

synthesized pool only.


111

Of special interest are a group of recently developed SNAP-substrates

that display a dramatic increase in fluorescence after reaction with SNAP.

These so called ‘dark-dyes’ are either quenched by guanine itself (Stöhr et al,

2010), or by a side-group fused the guanine moiety of benzylguanine

(Komatsu et al, 2011; Sun et al, 2011). These dark-dyes provide a number of

advantages over traditional fluorescent SNAP-substrates, most importantly

leading to highly reduced (unspecific) background fluorescence. Other

advantages include wash-free labeling, faster downstream applications (due

to shorter wash steps), and potentially more efficient live cell imaging.

Table 2.2 Selection of SNAP-Substrates

1: Fluorescent BG substrates are labeled to a second sidegroup that quenches the fluorescence by FRET. After protein labeling, the two sidegroups are spatially removed and leading to fluorescence activation. 2: Idem above, except that fluorophores are used that are naturally quenched by guananine, alleviating the need for adding a second (bulky) sidechain. 3: One reason to use these dyes for superresolution microscopy, is their increased brightness as compared to FPs; a limiting factor for these techniques.

SNAP labeling: enzyme variant

Variants of SNAP have been derived by in vitro evolution. One example

is the “CLIP-tag”, which is derived from SNAP and reacts specifically with a

variant substrate, O2-benzylcytosine (Gautier et al, 2008). Tagging of two

different proteins by SNAP and CLIP allows for simultaneous labeling of two

different proteins in different colors (Gautier et al, 2008; Prendergast et al,

Type of SNAP-substrate labels Examples Specifications References

Quenchers BG, BTPUsed to block (quench) pre-existing pools of SNAP protein to

prevent their detection in subsequent labeling stepsNEB, cat# S9106S

Fluorescent substrates

Standard fluorophores TMR-Star, BG-505 Used for most microscopy based pulse-labeling techniques.NEB, cat# S9105S;

S9105S

Dark dyes (induced quenching)1 DRBGFL, CBG-549-

QSY7

Used for reduced backgrounds, which allows for wash-free

labeling and this a faster labeling procedure

Komatsu et al, 2011; Sun

et al, 2011

Dark dyes (natural quenching)2 BG-MR121Used for reduced backgrounds, which allows for wash-free

labeling and this a faster labeling procedureStöhr et al, 2010

Caged dyes BG-CMNB-cagedSubstrate that becomes fluorescent after UV-activation (similar to

photo-activatable fluorescent proteins)Campos et al, 2011

Superresolution dyes (double-dyes)3 BG-Cy3-Cy5 Used for PALM/STORM of SNAP labeled proteins Dellagiacoma et al, 2011

Protein purification substrates

BeadsBG-Beads (agarose or

magnetic)Used for biochemical purification of SNAP labeled proteins

NEB, cat# S9144S;

S9145S

Biotinylation BG-BiotinUsed for biochemical purification of SNAP labeled proteins using

streptavidin beadsNEB, cat# S9110S

Other types of Dyes

Drugs BG-THL Used to deliver drugs to subcellular compartments Yang et al, 2011

Thiol BG-ThiolUsed to create self-assembling-monolayers (SAM) of SNAP-labeled

proteinsKwok et al, 2011

More ….

Chapter 2

112

2011). More recently, variants of SNAP and CLIP named SNAPf and CLIPf

have been developed that present faster reaction kinetics (Pellett et al., 2011;

Sun et al., 2011). We evaluated SNAPf and CLIPf performance in vivo by

side-by-side comparison with SNAP and CLIP, using the intracellular

protein CENP-A as a labeling target (data not shown and Figure 2.7A).

While CLIPf showed only a modest improved over CLIP (not shown), SNAPf

performed ~3-5 fold better across different concentrations of substrates and

incubation times (Figure 2.7B). The use of SNAPf therefore allows for

shorter labeling times and lower dye concentrations to yield the same signal

intensity. A reduced background staining while retaining specific signals will

potentially improve live cell capabilities significantly.

Figure 2.7 Evaluation of SNAPf-tag performance. (A) HeLa cells were transfected with either CENP-A-SNAP or

CENP-A-SNAPf fusion proteins, and labeled with TMR-Star at different concentrations and incubation times, as

indicated in the figure. Representative images of cells are shown with TMR-Star signals in green and DAPI (DNA) in

blue. (B) TMR-Star and HA fluorescence intensity were determined using CRaQ (Basic Protocol 5) and TMR-Star/HA

ratios are used as a measure of SNAP or SNAPf activity. Results are plotted as fold difference, normalized to signals

obtained with SNAP after incubation with 2μM TMR-Star for 15 minutes (standard conditions). SNAPf outperforms

SNAP in all conditions tested (3-5 fold).


113

SNAP labeling: Dye concentration, wash steps, and pool size:

Depending on the cell type, expression levels, application, SNAP-

substrate, etc., it is necessary to optimize substrate concentrations. Higher

concentrations are not always preferable, as this can result in higher

background levels and thus poorer signal-to-noise ratios. For CENP-A-

SNAP we generally use a concentration of 2 μM TMR-Star as a compromise

between signal-to-noise and cost (although we have found that using higher

concentrations up to 5 μM increases the signal-to-noise ratio of labeling).

For other purposes it may be necessary to use saturating concentrations, or

conversely, it may be sufficient to use lower concentrations.

We found that extensive washes after labeling (2 quick washes, an

extended wash for 30 minutes at 37°C, and two additional quick washes)

help to remove excess unbound substrates. This results in dramatically

decreased background fluorescence after pulse labeling. During quench

labeling these wash steps ensure that nascent protein synthesized during the

chase is not immediately quenched which would lower the effective poolside

of the new pool and specific signals in subsequent fluorescent labeling.

SNAP labeling: Chase time

A critical aspect of a successful quench-chase-pulse experiment is the

chase time that the cells are given to produce new protein. Although this is

largely determined by the experimental conditions, one would typically seek

conditions that maximizes the time for protein synthesis prior to labeling.

Imaging and quantification: Microscope

For imaging of SNAP-derived and immunofluorescent signals any high

resolution microscope can be used.

Imaging and quantification: Reference marker

Special care should be taken to choose the marker used as a reference for

spot detection. A number of options exist. 1) The signals that require

quantification can be used simultaneously as a reference of spots to

Chapter 2

114

measure. However, this solution suffers from the drawback that spots with

very low signals will not be detected and that the detection will be inherently

biased, e.g. towards bright spots. A better option is to 2) use an antibody

against SNAP (available from NEB) or HA (in case an HA-tag is

incorporated in the fusion protein; see Appendix), which will detect the

entire pool of SNAP tagged protein independent of time sliced signals (see

e.g. Figure 2.3B and 2.4B). However, if the protein of interest forms

aggregates or has multiple possible localization patterns, these will also be

quantified by automated methods such as CRaQ. Thus, whenever possible,

we prefer to use 3) antibodies (or autofluorescent fusion proteins) against an

independent marker for the subcellular structure (e.g. centromeres by

CENP-C or CENP-T; see Figures 2.2B, 2.4C, and Silva et al., 2012). This

allows for specific and unbiased detection of spots. Naturally, clean

references will lead to the most accurate quantifications and using

antibodies that are highly specific and give little background staining will

increase the quality of the data. In addition, when measuring proteins that

reside inside the nucleus, an additional marker such as DAPI can be used to

further exclude unspecific reference signals outside of the nucleus.

Imaging and quantification: CRaQ

There are a number of critical aspects to take into account when using

CRaQ. First and foremost, as this is an automated algorithm, the results

should be validated by the user. After initiating the macro one can follow the

screen shots that pop up to monitor which spots are recognized as reference

points. If the macro is poorly tuned it may already be obvious at this early

stage (e.g. recognition of the entire image). Next, after completion of the

macro, data output files should be checked to validate whether the correct

spots are detected (e.g. by doing this manually for a small, random subset of

pictures and comparing this to the spots recognized automatically). If

automated spot recognition is not accurate, the parameters should be

optimized as described in Basic Protocol 5. Parameter optimization and

testing is best done on a small subset of pictures to save time.


115

Evidently, using a high-end microscope with appropriate filter

combinations and a sensitive camera is instrumental to obtain good

fluorescence quantifications. In addition, potential chromatic aberrations

between reference and data channels must be corrected for in the

quantification (this can also be set as a parameter of CRaQ). One way to

determine the chromatic aberration is to use beads that are fluorescent in

the two channels used and determine whether and by how many pixels the

center of mass is shifted between the colors.

Finally, although inorganic dyes are generally very photostable, we have

observed that imaging TMR-Star labeled cells as soon as possible after

fixation (1–2 days) facilitates obtaining the most optimal signals.

Anticipated Results

SNAP-labeling

Because SNAP substrates are added to the culture medium, virtually all

SNAP-expressing cells are labeled in any given experiment. The ability to

detect SNAP-tagged proteins depends on the expression level of the protein

and the efficiency of SNAP substrate entry into the cells. In quench-chase-

pulse experiments, the chase time during which cells synthesize and

assemble new protein will determine which cells will become labeled during

the second, fluorescent labeling step. In the case of CENP-A-SNAP, the

appearance of centromeric signals will largely depend on cell cycle position

(Figure 2.4B and 2.5). The expected results for other proteins will depend on

the biological properties of the protein of interest.

Many SNAP-substrates have difficulty passing through the cell

membrane. For this reason it is normal to see relatively high background

fluorescence, as compared to e.g. antibody or fluorescent protein detection.

We try to minimize this background fluorescence by extensive washes of the

fluorescent substrate after labeling is completed (steps e.g. 5–6 of Basic

Protocol 1).

Chapter 2

116

Image quantification

Using CRaQ we generally have very low false-positive rates, where off-

target sites or doublets comprise ≪1% of all spots detected. In addition, this

macro is generally able to detect a good proportion of the correct spots to be

analyzed (>50%), although this largely depends on the quality of the

reference signal. Using a generic present day desktop computer we can

readily collect hundreds to thousands of data points in 15-20 minutes. The

rate limiting steps are testing parameter settings (although generic

parameter settings usually work very well) and analyzing the data generated.

Time considerations

The time that is required for the experiments outlined above is highly

variable and depends on the precise setup of the experiment. Quench and

pulse labeling each take about 1–1.5h to perform. However, the chase time

can be anywhere between a few hours and a few days. Furthermore, adding

sequential steps, such as synchronization and/or RNAi procedures can

increase the total time of the experiment to more than a week. Fixation and

antibody labeling requires approximately 4–5 hours to perform and cells are

preferentially imaged on the following day. Imaging requires roughly 30

minutes per coverslip used, although this again depends on many factors,

including the microscopy system, signal intensity (i.e. exposure times

needed), cell density (i.e. number of images required), sample thickness (i.e.

number of slices required), etc. Running CRaQ generally takes no more than

20 minutes, even for large datasets, and validation of the output takes about

the same time. Finally, processing of the output data into comprehensible

tables/graphs takes about 30 minutes to 1 hour, depending on the size of the

dataset.


117

REFERENCES

Bojkowska K, Santoni de Sio F, Barde I, Offner S, Verp S, Heinis C, Johnsson K & Trono D (2011) Measuring in vivo protein half-life. Chem. Biol. 18: 805–815

Burns JC, Friedmann T, Driever W, Burrascano M & Yee JK (1993) Vesicular stomatitis virus G glycoprotein pseudotyped retroviral vectors: concentration to very high titer and efficient gene transfer into mammalian and nonmammalian cells. Proc. Natl. Acad. Sci. U. S. A. 90: 8033–8037

Campos C, Kamiya M, Banala S, Johnsson K & González-Gaitán M (2011) Labelling cell structures and tracking cell lineage in zebrafish using SNAP-tag. Dev. Dyn. Off. Publ. Am. Assoc. Anat. 240: 820–827

Damoiseaux R, Keppler A & Johnsson K (2001) Synthesis and applications of chemical probes for human O6-alkylguanine-DNA alkyltransferase. Chembiochem Eur. J. Chem. Biol. 2: 285–287


Erhardt S, Mellone BG, Betts CM, Zhang W, Karpen GH & Straight AF (2008) Genome-wide analysis reveals a cell cycle-dependent mechanism controlling centromere propagation. J. Cell Biol. 183: 805–818

Gautier A, Juillerat A, Heinis C, Corrêa IR, Kindermann M, Beaufils F & Johnsson K (2008) An engineered protein tag for multiprotein labeling in living cells. Chem. Biol. 15: 128–136


Juillerat A, Gronemeyer T, Keppler A, Gendreizig S, Pick H, Vogel H & Johnsson K (2003) Directed evolution of O6-alkylguanine-DNA alkyltransferase for efficient labeling of fusion proteins with small molecules in vivo. Chem. Biol. 10: 313–317

Keppler A, Arrivoli C, Sironi L & Ellenberg J (2006) Fluorophores for live cell imaging of AGT fusion proteins across the visible spectrum. BioTechniques 41: 167–170, 172, 174–175

Keppler A, Gendreizig S, Gronemeyer T, Pick H, Vogel H & Johnsson K (2003) A general method for the covalent labeling of fusion proteins with small molecules in vivo. Nat. Biotechnol. 21: 86–89

Keppler A, Pick H, Arrivoli C, Vogel H & Johnsson K (2004) Labeling of fusion proteins with synthetic fluorophores in live cells. Proc. Natl. Acad. Sci. U. S. A. 101: 9955–9959

Komatsu T, Johnsson K, Okuno H, Bito H, Inoue T, Nagano T & Urano Y (2011) Real-time measurements of protein dynamics using fluorescence activation-coupled protein labeling method. J. Am. Chem. Soc. 133: 6745–6751

Maduzia LL, Yu E & Zhang Y (2010) Caenorhabditis elegans Galectins LEC-6 and LEC-10 Interact with Similar Glycoconjugates in the Intestine. J. Biol. Chem. 286: 4371–4381

Chapter 2

118

McMurray MA & Thorner J (2008) Septin stability and recycling during dynamic structural transitions in cell division and development. Curr. Biol. CB 18: 1203–1208

O’Hare HM, Johnsson K & Gautier A (2007) Chemical probes shed light on protein function. Curr. Opin. Struct. Biol. 17: 488–494

Prendergast L, van Vuuren C, Kaczmarczyk A, Doering V, Hellwig D, Quinn N, Hoischen C, Diekmann S & Sullivan KF (2011) Premitotic assembly of human CENPs -T and -W switches centromeric chromatin to a mitotic state. PLoS Biol. 9: e1001082


Stöhr K, Siegberg D, Ehrhard T, Lymperopoulos K, Öz S, Schulmeister S, Pfeifer AC, Bachmann J, Klingmüller U, Sourjik V & Herten D-P (2010) Quenched substrates for live-cell labeling of SNAP-tagged fusion proteins with improved fluorescent background. Anal. Chem. 82: 8186–8193

Sullivan KF, Hechenberger M & Masri K (1994) Human CENP-A contains a histone H3 related histone fold domain that is required for targeting to the centromere. J. Cell Biol. 127: 581–592

Sun X, Zhang A, Baker B, Sun L, Howard A, Buswell J, Maurel D, Masharina A, Johnsson K, Noren CJ, Xu M-Q & Corrêa IR (2011) Development of SNAP-Tag Fluorogenic Probes for Wash-Free Fluorescence Imaging. Chembiochem 12: 2217–2226

Waterman-Storer CM & Salmon ED (1997) Actomyosin-based Retrograde Flow of Microtubules in the Lamella of Migrating Epithelial Cells Influences Microtubule Dynamic Instability and Turnover and Is Associated with Microtubule Breakage and Treadmilling. J. Cell Biol. 139: 417 –434

Yee JK, Miyanohara A, LaPorte P, Bouic K, Burns JC & Friedmann T (1994) A general method for the generation of high-titer, pantropic retroviral vectors: highly efficient infection of primary hepatocytes. Proc. Natl. Acad. Sci. 91: 9564 –9568

Author contributions

All experiments and protocols described have been executed, designed

and/or optimized by me and LETJ, with the following exceptions: MGR

performed experiments shown in Figure 2.7; NM created an initial macro

that I further developed into CRaQ (Basic Protocol 5). The manuscript for

this chapter was drafted and revised with help of LETJ and constructive

suggestions by all authors.


119

Acknowledgements

We thank Mariana Silva for valuable comments on the manuscript. DLB

and MGR are supported by the Fundação para a Ciência e a Tecnologia

(FCT) doctoral fellowships SFRH/BD/74284/2010 and

SFRH/BD/33567/2008, respectively. This work is supported by the

Fundação Calouste Gulbenkian, FCT grants BIA-BCM/100557/2008 and

BIA-PRO/100537/2008, the European Commission FP7 programme, and

an EMBO installation grant to LETJ.

Chapter 2 - Appendix

120

Appendix: Maps of SNAP- and SNAPf-tags

SNAP constructs

121


122

CHAPTER 3

Assembly in G1 phase and Long-Term Stability are

Unique Intrinsic Features of CENP-A Nucleosomes

Dani L. Bodor1, Luis P. Valente1, João F. Mata1, Ben E. Black2, and Lars E.T. Jansen1

1 Instituto Gulbenkian de Ciência, 2780-156, Oeiras, Portugal.

2 University of Pennsylvania, Philadelphia, PA 19104-6059, USA.

NB: This chapter is a near literal transcription of Mol. Biol. Cell April 1, 2013 vol. 24

no. 7 pp. 923-932. Noteworthy is the addition of unpublished results for depletion of

M18BP1 in Figure 3.5 and accompanying text.

NB2: Unpublished results concerning depletion of CENP-C have been added in an

appendix to this chapter.

ABSTRACT

Centromeres are the site of kinetochore formation during mitosis.

CENP-A, the centromere specific histone H3 variant is essential for the

epigenetic maintenance of centromere position. Previously, we have shown

that newly synthesized CENP-A is targeted to centromeres exclusively

during early G1 phase and is subsequently maintained across mitotic

divisions. Using SNAP-based fluorescent pulse labeling, we now

demonstrate that cell cycle restricted chromatin assembly at centromeres is

unique to CENP-A nucleosomes and does not involve assembly of other H3

variants. Strikingly, stable retention is restricted to the CENP-A/H4 core of

the nucleosome which we find to outlast general chromatin across several

cell divisions. We further show that cell cycle timing of CENP-A assembly is

independent of centromeric DNA sequences, but instead is mediated by the

CENP-A targeting domain. Unexpectedly, this domain also induces stable

transmission of centromeric nucleosomes, independent of the CENP-A

deposition factor HJURP. This demonstrates that intrinsic properties of the

CENP-A protein direct its cell cycle restricted assembly and induces

quantitative mitotic transmission of the CENP-A/H4 nucleosome core

ensuring long-term stability and epigenetic maintenance of centromere

position.

Defining the heritable centromere core

127

INTRODUCTION

Centromeres are the chromosomal loci for kinetochore formation during

mitosis and thus form the site of interaction between DNA and the mitotic

spindle (Cheeseman & Desai, 2008). As a result, centromeres are essential

for proper chromosome segregation and prevention of aneuploidy. Although

human centromeres are usually assembled on alpha-satellite (alphoid) DNA,

specific sequences are neither necessary nor sufficient to stably maintain a

centromere. Evidence for this comes primarily from the existence of

neocentromeres, where a specific centromere has repositioned to, and is

stably maintained upon a naive locus that differs in DNA sequence context

and is not normally associated with centromere activity (Amor et al, 2004;

Marshall et al, 2008; Voullaire et al, 1993). This has led to the proposal that

centromeres are specified in a sequence independent, epigenetic manner.

While the vast majority of genomic DNA is packed by the canonical

histones (H2A, H2B, H3.1, and H4), specific histone H3 variants package

subsets of the genome. Among these, the H3.3 variant is mainly found at

sites of active transcription (Ahmad & Henikoff, 2002), while centromere

protein A (CENP-A) replaces H3.1 specifically in centromeric nucleosomes

(Yoda et al, 2000; Foltz et al, 2006), and is required for the localization of

nearly all other centromeric proteins (Foltz et al, 2006; Liu et al, 2006).

Consistent with a role in epigenetic maintenance of centromere identity,

CENP-A is a stable component of centromeric chromatin (Pearson et al,

2004; Schuh et al, 2007; Hemmerich et al, 2008) and is transmitted at

centromeres during successive cell divisions (Jansen et al, 2007). In

addition, it was recently shown in Drosophila S2 cells that targeting of

CENP-ACID to ectopic loci for a short period of time is sufficient to initiate a

sustainable epigenetic feedback loop, which recruits and maintains

functional kinetochores for several subsequent cell division cycles

(Mendiburo et al, 2011). Together, these findings strongly suggest that

CENP-A plays a key role in epigenetic memory of centromere position and

function.

Chapter 3

128

Consistent with a critical role in centromere specification, assembly of

CENP-A is tightly regulated and restricted to a specific stage in the cell cycle

in order to maintain proper CENP-A levels. In metazoans, assembly of

CENP-A is uncoupled from S phase and dependent on passage through

mitosis (Jansen et al, 2007; Schuh et al, 2007; Moree et al, 2011; Mellone et

al, 2011; Bernad et al, 2011). We have previously shown that G1 phase

restricted assembly of CENP-A in human and chicken cells is directly

coupled to cell cycle progression as a result of inhibitory action of Cdk1 and

Cdk2 in S phase, G2, and mitosis (Silva et al, 2012). While we have a basic

understanding of the mechanism of cell cycle coupling of centromeric

chromatin assembly, how this assembly is restricted to centromeres and how

CENP-A chromatin is stably maintained is unclear.

In this study we determine whether centromeric chromatin assembly

during G1 represents a general phase of nucleosome turnover, or whether

this is a unique feature of CENP-A nucleosomes. In addition, we determined

whether the previously reported stable maintenance of CENP-A (Jansen et

al, 2007) is a feature of centromeric chromatin in general, or whether this is

an intrinsic property of CENP-A-containing nucleosomes or even

subnucleosomal complexes thereof. Using SNAP-tag based fluorescent pulse

labeling (Jansen et al, 2007; Bodor et al, 2012; Silva et al, 2012), we made

the striking finding that CENP-A nucleosome assembly is the major form of

nascent chromatin assembly in G1. This results in the formation of

nucleosomes with a uniquely high in vivo stability of the CENP-A/H4

nucleosome core, a property induced in cis by residues encoded by the

CENP-A protein.


129

RESULTS

G1 phase histone assembly is restricted to CENP-A and H4.

We have previously used SNAP labeling to demonstrate that

incorporation of nascent CENP-A is restricted to a brief window during early

G1 phase (Jansen et al, 2007). SNAP is a self-labeling suicide enzyme that

covalently and irreversibly reacts with benzylguanine or (fluorescent)

derivatives thereof (Keppler et al, 2003, 2004). Sequential SNAP labeling

steps allow for differential analysis of protein pools synthesized at distinct

periods of time (Bodor et al, 2012). Timing of CENP-A assembly can be a

consequence of an intrinsic property of this particular protein, or result from

a general wave of histone exchange at centromeres during G1. To determine

whether a G1 assembly pathway exists for other histones, we used cells

stably expressing SNAP-tagged versions of a variety of histone proteins.

These include two other histone H3 family members, the canonical H3.1 and

the replacement variant H3.3, as well as H4, the direct binding partner of all

H3 variants, and H2B, a member of the more dynamic H2A/H2B histone

sub-complex (Kimura & Cook, 2001). Direct pulse labeling of the total

(steady state) pool of SNAP-tagged histone showed signal in all cells, as

expected (Figure 3.S1A–B). To determine the pattern of assembly of nascent

histones, we performed SNAP-based quench-chase-pulse experiments

[Figure 3.1A and (Bodor et al, 2012)]. To visualize stable chromatin

assembly of nascent protein we pre-extracted cells prior to fixation and

imaging (Ray-Gallet et al, 2011). As anticipated, due to cell cycle regulated

assembly, nascent CENP-A-SNAP is found at centromeres in only a subset of

cells [Figure 3.1B and (Jansen et al, 2007)]. Similarly, nascent H3.1-SNAP is

found in a subset of the population (Figure 3.1B), owing to its strict

replication-coupled assembly (Ray-Gallet et al, 2011). Interestingly, distinct

sub-nuclear patterns of H3.1-SNAP staining can be observed, indicative of

differential patterns of DNA-synthesis throughout S phase [Figure 3.1B and

(Ray-Gallet et al, 2011)]. These results emphasize the power of SNAP-based

Chapter 3

130

pulse-chase assays as they reveal strikingly different patterns of localization

of the same protein, but synthesized and deposited into chromatin at

different times during the cell cycle. Our H3.1-SNAP cell line therefore

provides a powerful and accessible tool for marking S phase progression

without the need for an inducible expression system. In contrast, H3.3 (Ray-

Gallet et al, 2002, 2011) and H2B (Kimura & Cook, 2001) are assembled

throughout the cell cycle and, consequently, nascent protein can be observed

in all cells analyzed (Figure 3.1B).

Intriguingly, nascent H4-SNAP reveals a unique differential pattern of

assembly, different from all other histone proteins analyzed. While all cells

display assembly throughout chromatin, consistent with a role as partner of

H3.1 in S phase or H3.3 throughout the cell cycle, preferential assembly at

discrete foci is observed in a subset of cells (Figure 3.1B). This pool of

nascent H4 specifically colocalizes with centromeres, as marked by CENP-C

(Figure 3.1B, enlargement), suggesting that histone H4 has a distinct phase

of centromeric assembly.

CENP-A and H4 are co-assembled during G1 phase.

Prenucleosomal CENP-A forms a complex with H4 and HJURP, the

CENP-A specific histone chaperone (Foltz et al, 2009; Dunleavy et al, 2009;

Hu et al, 2011; Shuaib et al, 2010). In addition, the CENP-A/H4 interface

forms a highly rigid structure in nucleosomes (Black et al, 2007a) as well as

in prenucleosomal (CENP-A/H4)2 tetramers (Black et al, 2004) and

CENP-A/H4/HJURP trimers (Bassett et al, 2012). Thus, we reasoned that

centromere specific assembly of H4 results from co-assembly with CENP-A

during G1 phase in vivo. To test this directly, we labeled nascent pools of

SNAP-tagged CENP-A, H3.1, H3.3, H2B and H4 in cells synchronized in G2

phase of the cell cycle and analyzed assembly in the subsequent G1 phase

(Figure 3.1C). Only CENP-A and H4-SNAP are assembled at centromere foci

indicating that centromeric assembly of H4 is contemporaneous with

CENP-A (Figure 3.1D).


131

Figure 3.1 H4, but not H3.1, H3.3 or H2B are co-assembled with CENP-A in G1 phase. (A) Outline of quench-chase-

pulse labeling strategy, allowing visualization of a newly synthesized pool of SNAP, followed by Triton based pre-

extraction. (B) Results of A for indicated histone-SNAP fusion proteins. Enlargement to the right shows rescaled images

to indicate colocalization of newly synthesized H4-SNAP with centromeres (marked by CENP-C). Enlargements below

show single focal plane images to indicate specific subnuclear assembly patterns. Blue, green, and red arrows show G1,

early S, and mid/late S phase cells, respectively. (C) Outline of quench-chase-pulse experiment on synchronized cells.

(D) Results of C for SNAP tagged histone proteins. CENP-C staining indicates centromere positions. Enlargement

shows colocalization of newly synthesized H4-SNAP with centromeres.

Chapter 3

132

Importantly however, while nascent CENP-A-SNAP and H4-SNAP

colocalize at centromeres, newly synthesized H3.1-, H3.3-, and H2B-SNAP

remain diffusely localized (Figure 3.1D). This indicates that these histones

are not preferentially assembled at centromeres at this stage. Importantly,

this does not exclude the possibility that H2B is part of the centromeric

nucleosome, nor that any of these histones are incorporated into centro-

meric chromatin at this time, albeit at a rate that is similar to the genome

overall. This result, however, does demonstrate that the centromere is not a

specialized chromatin domain that undergoes major nucleosome turnover

events during G1 phase. Rather, CENP-A and H4 form a subnucleosomal

core, which is specifically assembled at centromeres during G1 phase.

Figure 3.2 Assembly of CENP-A and H4 depends on passage through mitosis. (A) Outline of quench-chase-pulse in

unperturbed cells, or combined with nocodazole treatment, or nocodazole treatment and washout. (B) Results of A for

CENP-A-SNAP and H4-SNAP. Cyclin B and tubulin staining indicate G2 and G1 (midbodies) status, respectively. (C)

Quantification of B. ~200–300 cells were analyzed for each condition. Note that during the 8 hour chase, cells transit

through ~40% of the 22 hour cell cycle indicating the maximum expected percentage of cells entering G1 phase.


133

To validate that centromeric enrichment of H4 is not a consequence of

the SNAP labeling procedure, we created a polyclonal HeLa cell line

expressing H4-YFP. While endogenous pools of H4 are oscillating along the

cell cycle, peaking in S phase (Marzluff & Duronio, 2002), the YFP tagged

H4 transgene, like our SNAP-tagged H4, is expressed at a constitutive level.

Consequently, the relative levels of tagged versus endogenous H4 are higher

in G1 phase than in S phase. For this reason we expect that tagged H4 can be

detected at centromeres, despite genome wide assembly in S phase, even

without pulse-chase labeling. Indeed, when cells express low levels of H4-

YFP, centromeric enrichment of this fusion protein can be detected over

general chromatin (Figure 3.S1C), corroborating our observations with the

SNAP-tag.

Next, we determined whether centromeric H4 assembly depends on G1

phase entry. For this, we labeled nascent proteins either in an asynchronous

population of cells or in cells which were prevented from exiting mitosis by

addition of nocodazole (Figure 3.2A). After an 8 hour synthesis period, both

CENP-A-SNAP and H4-SNAP readily assembled at centromeres in a subset

of unperturbed cells. None of these cells stained positive for Cyclin B (Figure

3.2B–C), indicating that no centromere assembly occurred in late S, G2, or

M phase. Consistently, virtually no cells assembled CENP-A or H4 when

entry into G1 was prevented by addition of nocodazole in asynchronous cells

(Figure 3.2B–C) or in a G2 synchronized population (Figure 3.S2E–F).

However, nocodazole treatment or consequent mitotic arrest do not

irreversibly prevent assembly, as release into G1 by nocodazole washout

promptly resulted in centromere targeting of CENP-A-SNAP and H4-SNAP,

exclusively in Cyclin B negative cells (Figure 3.2B–C). Analysis of cells

synchronized at different stages along the cell cycle confirm that enrichment

of nascent H4-SNAP at centromeres is only observed if cells cycle through

G1 (Figure 3.S2) indicating that assembly of this histone at centromeres is

uniquely restricted to this phase. We conclude that CENP-A and H4

assemble contemporaneously, in a manner dependent on mitotic exit. In

Chapter 3

134

addition, since G1 assembly of H4 is largely restricted to centromeres, our

data strongly suggest that nucleosome assembly (of other H3 variants)

throughout the rest of the genome represent a minority of assembly at this

stage of the cell cycle. Thus, while only representing at most ~2% the total

number of all nucleosomes (Black et al, 2007b), CENP-A nucleosome

deposition represents the major form of chromatin assembly in G1.

Together, these results strongly suggest that CENP-A and H4 represent

the centromeric nucleosome core, which is assembled as a pre-formed

complex during early G1 phase by the CENP-A loading machinery. The

absence of foci of nascent H3.1, H3.3, and H2B indicates that these proteins

are not preferentially assembled at centromeres, arguing against general

chromatin reorganization during G1 phase.

Quantitative retention of the centromeric nucleosome core.

Once incorporated into centromeric chromatin, CENP-A is stably

transmitted as cells divide (Jansen et al, 2007) and diluted among nascent

sister chromatids during S phase (Dunleavy et al, 2011). To test whether this

is also true for other histones at the centromere, we performed pulse-chase

experiments of SNAP-tagged proteins (Figure 3.3A). SNAP-based

fluorescent pulse labeling followed by a chase period determines the

turnover rate of the labeled protein pool in vivo (Jansen et al, 2007; Bodor

et al, 2012). Remarkably, both CENP-A and H4 retain centromeric

enrichment for the duration of the experiment (72 hours; Figure 3.3B), and

can still be observed at even longer timescales (up to 120 hours for CENP-A

and 96 hours for H4; Figure 3.S3A). To determine the relative stability of

centromere enriched histones, we quantified centromeric and non-

centromeric TMR-Star fluorescence intensity as a measure of the amount of

protein remaining at different time points (Figure 3.3C and see methods).

Strikingly, we find that centromeric pools of CENP-A and H4 are

considerably more stable than H3.1 (Figure 3.3D). Moreover, while H3.1

turnover is indifferent to centromere localization, the centromeric pool of


135

H4 has an increased stability compared to H4 outside of the centromere

(Figure 3.3D), indicating that CENP-A/H4 containing nucleosomes are

preferentially stabilized compared to general chromatin.

Similar to H3.1, no specific stability of H2B or H3.3 was observed at

centromeres (Figure 3.S3B). This indicates that H2A/H2B dimers exchange

on centromeric nucleosomes at similarly high rates as on conventional

nucleosomes in bulk chromatin. Moreover, considering that intervening

H3.1 and H3.3 nucleosomes are present at centromeres (Blower et al, 2002;

Dunleavy et al, 2011), we find that long-term retention of chromatin is

restricted to the CENP-A/H4 core of CENP-A nucleosomes with H3.1/H3.3

nucleosomes turning over at higher rates.

Timing of assembly and stable retention of the centromeric

nucleosome core is controlled by the CENP-A targeting domain.

While centromeres are maintained epigenetically, the unusual properties

of CENP-A nucleosomes we uncovered may be dependent on local sequence

features at centromeres. Alternatively, timing of centromere assembly and

stable retention of CENP-A nucleosomes could be directed in cis by CENP-A

itself.

The CENP-A targeting domain (CATD), encompassing the L1 loop and

α2 helix of the CENP-A histone fold domain, plays a pivotal role in the

definition of centromeric chromatin. Replacement of the corresponding

domain of canonical H3 with the CATD of CENP-A is sufficient to target the

chimeric H3CATD to both canonical centromeres (Black et al, 2004, 2007b)

and neocentromeres (Bassett et al, 2010). Furthermore, binding of

prenucleosomal CENP-A to its histone chaperone HJURP is mediated

through the CATD (Black et al, 2004; Foltz et al, 2009; Shuaib et al, 2010;

Bassett et al, 2012). HJURP is itself recruited to centromeric chromatin in

early G1 (Foltz et al, 2009; Dunleavy et al, 2009).

Chapter 3

136

Figure 3.3 CENP-A and H4 are preferentially maintained at centromeres. (A) Outline of pulse-chase experiment

allowing for analysis of a pre-incorporated pool of SNAP for up to 72 hours. At each time point, cells were counted to

allow accurate quantification of SNAP turnover per cell division. (B) Results of A for CENP-A-SNAP, H4-SNAP and

H3.1-SNAP. Enlargements show rescaled images of remaining protein pool after 72 hours (see also Figure 3.S3A). (C).

Schematic outline for calculation of histone half-life. (D) Half-life measurements of centromeric and non-centromeric

histone pools as a function of time from experiment in B. Non-centromeric CENP-A is below detection and therefore not

measured. Data is obtained from between 570 and 1464 (centromeric) foci for each time point.


137

We decided to test directly whether, in addition to regulating centro-

meric targeting itself, the CATD is sufficient to dictate histone assembly

timing. When labeling a nascent pool of stably expressed H3CATD-SNAP we

detected centromeric H3CATD only in Cyclin B negative cells (Figure 3.4A–B),

suggesting that cells only load H3CATD into centromeres during G1 phase. In

addition, as for CENP-A and H4 (Figure 3.2A), prevention of mitotic exit by

nocodazole treatment abolished centromeric assembly of H3CATD-SNAP,

while release from this arrest resulted in mitotic exit and concomitant

assembly (Figure 3.4A–B). We conclude that, apart from centromere

localization, the CATD also mediates cell cycle control of CENP-A assembly.

Next, we determined whether long-term retention of CENP-A

nucleosomes at centromeres is also an intrinsic property of CENP-A. We

carried out pulse-chase experiments on H3CATD-SNAP expressing cells

(Figure 3.4C) and analyzed retention of H3CATD over time. As for CENP-A

and H4, pulse labeled H3CATD-SNAP remains detectable for multiple cell

divisions up to 120 hours following labeling (Figure 3.4D and 3.S3A). To

compare the stability of centromeric histones, we determined their rate of

turnover as a function of the number of cell divisions expressed as the half-

life (Figure 3.4E and see methods). In an extreme case where histones do

not turn over at all, loss of histone proteins would be expected to occur only

by redistribution among newly replicated sister chromatids during S phase

(replicative dilution). In this situation, we would find a 50% reduction of

fluorescence after each cell division (i.e. a histone half-life of exactly 1

division; Figure 3.4E, dashed line). For CENP-A-SNAP (experiment in

Figure 3.3), we observed a half-life of 1.07 ± 0.17 divisions (mean ± SEM is

indicated; Figure 3.4E), consistent with turnover by replicative dilution only.

Importantly, we observed very similar behavior for both H4-SNAP and

H3CATD-SNAP at centromeres, with half-lives of 0.94 ± 0.11 and 0.79 ± 0.12

divisions, respectively (Figure 3.4E). None of these values are significantly

different from a theoretical replicative dilution rate of 1 cell division (one-

tailed, one-sample t-test; n=3, α=0.05 in all cases).

Chapter 3

138

While the CATD has previously been implicated in rigidifying the

CENP-A/H4 interface within the nucleosome particle (Black et al, 2004,

2007a; Bassett et al, 2012; Sekulic et al, 2010) how this contributes to

CENP-A stability in vivo remained untested. Our results now show that

CENP-A confers long-term stability to the centromeric (CENP-A/H4)2

subnucleosome core and that this in vivo stability is encoded within the

residues that constitute the CENP-A targeting domain. This feature of

CENP-A ensures stable chromatin marking of centromeres across multiple

divisions.

Figure 3.4 CATD determines G1 phase assembly and stable transmission of CENP-A nucleosomes. (A–B) As in Figure

3.2 for H3CATD-SNAP. (C) As in Figure 3.3B for H3CATD-SNAP. (D) Determination of centromeric histone half-life as

a function of population doublings from experiments shown in Figure 3.3B and 3.4C. Dashed line (replicative dilution)

indicates expected values for proteins that are never lost, but merely redistributed as cells divide. Average and SEM of 3

independent experiments is shown.


139

Quantitative retention does not require HJURP or M18BP1.

We have shown that quantitative retention of CENP-A is, at least in part,

directed by the CATD. However, the mechanism by which the CATD

contributes to CENP-A stability remains unclear. To date, the most clearly

defined function of the CATD is to provide the binding interface for the

CENP-A chaperone HJURP (Foltz et al, 2009; Shuaib et al, 2010; Hu et al,

2011; Bassett et al, 2012). Interestingly, a proportion of endogenous HJURP

is stably chromatin bound (Foltz et al, 2006). This raises the possibility that

HJURP binding to CENP-A protects it from turning over, e.g. by binding to

chromatin incorporated CENP-A or by transiently chaperoning this histone

during the transition from parental chromosomes to daughter chromatids

during DNA replication. In addition, a severe reduction of centromeric

CENP-A levels was previously observed after depletion of M18BP1 (Maddox

et al, 2007), suggesting that this protein may have a role beyond CENP-A

assembly and contribute to its stable maintenance. To test this hypothesis

directly, we combined SNAP labeling experiments with RNAi against

HJURP and M18BP1 as detailed in Figure 3.5A.

As expected, nascent centromeric CENP-A-SNAP was readily observed in

all cells after siRNA mediated depletion of a control protein (GAPDH, Figure

3.5B). However, a large proportion of cells were unable to assemble nascent

CENP-A-SNAP after depletion of HJURP (Figure 3.5B), as has been

observed previously (Foltz et al, 2009). This result is consistent with the

known role of HJURP in the assembly of CENP-A during G1 (Barnhart et al,

2011). Similar results were found for M18BP1 (Figure 3.5B). Quantification

of centromeric signals shows that nascent CENP-A-SNAP levels are reduced

by ~50% after depletion of HJURP or M18BP1 (Figure 3.5C). Similar results

were obtained when RNAi was performed against CENP-A itself [Figure

3.5B–C and (Bodor et al, 2012)].

Chapter 3

140

Figure 3.5 HJURP and M18BP1 are dispensable for stable retention of CENP-A. (A) Outline of combined SNAP and

RNAi experiment. To minimize variation of RNAi efficiency, quench-chase-pulse and pulse-chase experiments were

done in parallel. (B) Results of A after depletion of indicated proteins. Images are displayed for nascent CENP-A-SNAP

and the pre-incorporated pool at 24 hours post RNAi. (C) Quantification of centromeric TMR-star fluorescence of

indicated CENP-A-SNAP pools after depletion of target proteins. Results were normalized against control RNAi

(GAPDH). Average and SEM for at least 3 independent experiments is shown. Asterisks and “NS” respectively indicate

statistically significant (p < 0.01) and non-significant (p > 0.05) differences from control samples in paired t-tests.

To test whether these loading factors are also involved in stabilizing

previously incorporated CENP-A nucleosomes, we combined pulse-chase

experiments with RNAi. Retention of CENP-A-SNAP at centromeres was

analyzed after target protein depletion for 24, 48, and 72 hours to allow for

assessment of both short- and long-term effects on CENP-A stability. In this

assay, centromeric CENP-A-SNAP could be observed in all cells analyzed

(Figure 3.5B) and no quantitative differences were observed between control


141

RNAi or depletion of HJURP, M18BP1, or CENP-A at any time point (Figure

3.5C). To ensure that we used conditions that effectively reduce protein

levels, these pulse-chase experiments were performed in parallel with the

quench-chase-pule experiments described above (Figure 3.5A). Our results

strongly suggest that HJURP is dispensable for stabilizing centromeric

CENP-A nucleosomes. We conclude that the long-term stability of the

CENP-A/H4 nucleosome core is due to an HJURP and M18BP1 independent

role of the CATD.

Timing of centromeric nucleosome assembly is independent of

alphoid DNA.

We have shown that the CATD of CENP-A is sufficient to direct G1 phase

restricted assembly of CENP-A chromatin suggesting that temporal loading

is dictated by the CENP-A protein itself. However, this does not exclude a

role for local sequence context being involved in regulating cell cycle timing.

Mammalian centromeres are assembled on arrays of alpha satellite DNA.

While overall centromere function is not strictly dependent on this DNA

sequence it may play a role in regulating centromere assembly and

maintenance. This is clear from efforts to produce centromeres de novo on

artificial chromosomes. While in some systems de novo centromeres can be

formed on any DNA (Yuen et al, 2011), success in mammalian cells has only

been reported with constructs containing large fragments of alphoid DNA

(Ohzeki et al, 2002). In addition, the inner centromere component Aurora B

was found to be mislocalized at a stably maintained human non-alphoid

containing neocentromere, resulting in an impaired mitotic error correction

mechanism (Bassett et al, 2010). Thus, although neocentromeres can exist

on non-alphoid DNA, the role of DNA sequences in maintenance of existing

centromeres remains elusive.

Chapter 3

142

Figure 3.6 Timing of CENP-A assembly is maintained at neocentromeres. (A) Cartoon of maternal (canonical

centromere) and paternal (neocentric) chromosome 4 in PD-NC4 cells. Indicated is chromosomal position 4q21.3, the

site of neocentromere formation and the hybridization site of the FISH probe used. (B) Outline of quench-chase-pulse

experiment in CENP-A-SNAP expressing PD-NC4 cells. (C–D) Results of B for cells in G1 phase (C) or G2 phase (D),

as indicated by nucleolar TMR staining, shown in rescaled inset). CENP-T indicates centromere positions. Enlargements

display images of the hybridization sites of the FISH probe. Green arrows indicate the neocentromere, while red arrows

show the homologous region on the maternal chromosome. (E) GFP-Mis18α expressing PD-NC4 cells were stained for

GFP and for 4q21.3 by FISH to detect Mis18α and the NeoCEN4, respectively. Enlargements as above. Paternal

(Neocentric) and maternal 4q21.3 positions are indicated by p and m, respectively, in C–E.


143

To determine the contribution of cis DNA elements in alphoid sequences

on the timing of CENP-A assembly, we stably expressed CENP-A-SNAP in

PD-NC4 (pseudodicentric-neocentric chromosome 4) cells. In these cells,

the centromere on the paternally inherited chromosome 4 (but not the

maternal one) has repositioned to chromosomal position 4q21.3, which does

not contain alphoid DNA sequences (NeoCEN4) [Figure 3.6A and (Amor et

al, 2004)]. By combining quench-chase-pulse experiments with FISH

against 4q21.3 (NeoCEN4) we were able to determine that CENP-A

assembly at neocentromeres occurred contemporaneously with canonical

centromeres of the same cell (Figure 3.6B–C). Importantly, although a

subset of cells displayed diffuse nucleolar staining, indicative of the

prenucleosomal pool of CENP-A in G2 phase (Jansen et al, 2007; Silva et al,

2012), CENP-A assembly was never observed at the NeoCEN4 alone, i.e.

when no assembly occurred on other centromeres (Figure 3.6D). To

corroborate these results, we stably expressed a GFP-tagged version of

Mis18α, an essential component of the Mis18 complex, in PD-NC4 cells.

Interestingly, one member of this complex, M18BP1, contains a Myb-domain

(Fujita et al, 2007; Maddox et al, 2007), a protein domain that is often

involved in site-specific DNA binding (Lipsick, 1996). Nevertheless, GFP-

Mis18α is consistently recruited to NeoCEN4 and alphoid DNA bearing

centromeres simultaneously (Figure 3.6E). Together, these results show that

CENP-A assembly at the NeoCEN4 occurs concurrently with canonical

centromeres, indicating that temporal control of the CENP-A assembly

machinery is maintained independently of alphoid DNA. This is consistent

with a dominant role for the CENP-A encoded CATD in directly controlling

temporal assembly of CENP-A chromatin.

Chapter 3

144

DISCUSSION

Maintenance of epigenetic identity requires the inheritance of structural

information from one cell generation to the next. Chromatin proteins and

their modifications have been implicated in such cellular memory (Talbert &

Henikoff, 2010; Gardner et al, 2011). However, transmission of chromatin-

based information faces many challenges throughout the cell cycle that may

disturb epigenetic inheritance, including nucleosome disruption during

DNA replication and chromatin (de)condensation during mitosis. Previous

work identified an atypical timing of assembly of CENP-A, as well as

centromere retention of the existing pool of CENP-A throughout the cell

cycle (Jansen et al, 2007). We now extend these findings and determined

that a distinct phase of centromeric loading in G1 as well as quantitative

centromeric retention is restricted to CENP-A and H4, rather than being a

general property of centromeric chromatin. Metabolic labeling experiments

and photo bleaching studies of GFP-tagged histones have previously

established that histone H3 and H4 are stable components whereas H2A

and H2B are more dynamic (Kimura & Cook, 2001; Xu et al, 2010).

However, apart from CENP-A itself (Jansen et al, 2007), locus specific

assembly and turnover has not been previously determined for these or

other histones. Our results now show that at the centromere, the

CENP-A/H4 form a stable subnucleosomal core that is quantitatively

retained throughout multiple cell divisions to maintain centromere identity

(Figure 3.7). Retention of H4 specifically at the centromere but not

elsewhere indicates that the centromeric CENP-A/H4 species is more stable

than general chromatin outlasting most, if not all, other nucleosome types.

Interestingly, many of the unique features of the CENP-A/H4

centromeric core are directed through the CATD region of CENP-A. It has

previously been shown that this region is responsible for 1) targeting of

CENP-A to centromeres (Black et al, 2004, 2007b) in a sequence

independent manner (Bassett et al, 2010); 2) binding to the CENP-A

specific histone chaperone HJURP (Foltz et al, 2009; Shuaib et al, 2010;


145

Bassett et al, 2012); 3) a unique, highly rigid, CENP-A/H4 dimerization

interface (Black et al, 2004; Bassett et al, 2012; Sekulic et al, 2010); and 4)

binding of CENP-N, which is in turn required for efficient centromeric

recruitment of nascent CENP-A (Carroll et al, 2009). In addition, we now

show that the CATD 5) is the element in CENP-A that mediates correct

timing of CENP-A assembly, independently of underlying DNA sequence

and that 6), critically, this region confers in vivo hyperstability to

centromeric nucleosomes in a manner independent of HJURP or M18BP1.

Importantly, parts of CENP-A outside of the CATD region have been shown

Figure 3.7 Model depicting unique features of centromeric nucleosomes. Cell cycle dynamics of different types of

nucleosomes are indicated. CENP-A nucleosomes are assembled at centromeres in G1 phase, while H3.1 and H3.3

nucleosomes are assembled into general chromatin in S phase and throughout the cell cycle, respectively (Ray-Gallet et al,

2011). Neither H3.1 nor H3.3 nucleosomes are preferentially loaded into centromeric chromatin during G1 phase or any

other cell cycle stage. While H2A and H2B are dynamic in all types of nucleosomes, the centromeric CENP-A/H4 core is

stable at time scales far surpassing the cell division rate. However, H3.1, H3.3, and non-centromeric H4 turn over more

rapidly than CENP-A, and no preferential centromeric maintenance of H3.1 or H3.3 is observed. Key to both temporal

assembly and stable transmission is the CATD domain of CENP-A that forms a stable interface with H4 in both CENP-A

and H3CATD nucleosomes (Sekulic et al, 2010; Bassett et al, 2012).

Chapter 3

146

to be required for kinetochore assembly, e.g. through binding of the

centromere protein CENP-C to the 6 most carboxy-terminal residues of

CENP-A (Guse et al, 2011; Carroll et al, 2010). Thus, while different domains

of CENP-A are likely to be involved in full centromere function, all of the key

properties of CENP-A for epigenetically maintaining centromere position

are mediated through the CATD.

Our results identify the CENP-A/H4 complex as the primary

components of the centromere that are selectively assembled each cell

division in a manner that leads to their long-term maintenance. A key future

challenge is to determine whether this unusual stability is an intrinsic

property of CENP-A nucleosomes or dependent on external factors that

ensure stable transmission of CENP-A and centromere identity.


147

MATERIAL & METHODS

Constructs and cell lines

Human H2B-SNAP, H4-SNAP, and H3CATD-SNAP constructs were

created by PCR cloning of histone ORFs into pSS26m (Covalys) to create C-

terminal SNAP fusion proteins. A triple hemagglutinin (3XHA) tag was

placed at the C-terminus of SNAP. Histone H4-YFP was generated by PCR

cloning of the human H4 ORF into pEYFP-N1 (Clontech) carrying Q69M

(citrin) and A206K (monomerization) mutations. The histone-SNAP-3XHA

and H4-YFP ORFs were subcloned into pBABE-Blast to generate retroviral

expression constructs. These constructs were delivered into HeLa cells via

Moloney murine leukemia retroviral delivery, as described previously

(Morgenstern & Land, 1990; Burns et al, 1993). Cells stably expressing the

SNAP fusion proteins were selected with 5 μg/ml blasticidin S (Calbiochem)

and were isolated and individually sorted by flow cytometry (except H4-YFP

which was analyzed as a polyclonal cell population). The resulting

monoclonal lines were selected for proper levels of the SNAP fusion proteins

by fluorescence microscopy after TMR-Star labeling. The following clones

were selected and used throughout this study: H2B-SNAP clone #5; H4-

SNAP clone #3; and H3CATD-SNAP clone #37. We previously described HeLa

monoclonal cell lines stably expressing H3.1-SNAP or H3.3-SNAP [clone #7

or #2, respectively; (Ray-Gallet et al, 2011)] or CENP‑A-SNAP [clone #23,

(Jansen et al, 2007)]. All HeLa cell lines were grown at 37°C and 5% CO2 in

DMEM containing 10% newborn calf serum, 2 mM L-glutamine, 100 U/ml

Penicillin and 100 μg/ml Streptomycin (henceforth referred to as complete

medium). In addition, SNAP expressing cells were maintained by addition of

1 μg/ml blasticidin S. PD-NC4 stable transgenic cell lines were created by

Moloney murine leukemia retroviral delivery of constructs expressing

CENP-A-SNAP (Jansen et al, 2007), or GFP-Mis18α (gift from Iain

Cheeseman) (Silva et al, 2012). PD-NC4 cells were grown at 37°C and 5%

CO2 in DMEM supplemented with 10% fetal calf serum, 2 mM L-glutamine,

Chapter 3

148

100 μg/ml neomycin, 100 U/ml Penicillin and 100 μg/ml Streptomycin.

Stable transgenic PD-NC4 lines were selected with 2,5 µg/ml Blasticidin

(CENP-A-SNAP) or 500 ng/ml Puromycin (GFP-Mis18α).

SNAP-labeling

SNAP labeling was performed essentially as described (Jansen et al,

2007; Bodor et al, 2012). Briefly, cells were labeled for 30’ with 2 μM BTP

(SNAP-Cell Block, New England Biolabs) or 15’ with 2 μM TMR-Star (New

England Biolabs) in complete medium, for quench or pulse labeling,

respectively, after which cells were washed twice with PBS and reincubated

with complete medium. After an additional 30 minutes, cells were washed

once more with PBS and either reincubated with complete medium, or fixed

and further treated for analysis, as indicated.

Cell synchronization and RNAi

Cells were synchronized in early S phase by double thymidine block as

described previously (Jansen et al, 2007; Bodor et al, 2012). Nocodazole was

used at a concentration of 500 ng/ml except for experiment in Figure 3.S2F

for which 200 ng/ml was used.

RNAi was performed in a 24-well format using 60 pm siRNAs using

Oligofectamine (Invitrogen) according to the manufacturer’s instructions.

All siRNAs were obtained from Dharmacon: SMARTpools were used to

deplete HJURP, M18BP1, and GAPDH; for CENP-A depletion siRNA target

5’-ACAGUCGGCGGAGACAAGG-3’ was used.

Immunofluorescence

Fixation, immunofluorescence, and DAPI staining of HeLa cells was

performed as described (Bodor et al, 2012). Pre-extraction was performed

for 5 minutes using 0.3% Triton X-100 (Sigma) in PBS prior to fixation.

Antibodies against CENP-C (mouse monoclonal), Cyclin B (sc-245, Santa

Cruz), and α-tubulin (YL1/2, Serotec) were used at a dilution of 1:10,000,


149

1:50, and 1:2,500, respectively. Fluorescent secondary antibodies were

obtained from Jackson ImmunoResearch and used at a dilution of 1:200.

Immuno-FISH

FISH was performed as previously described (Black et al, 2007a) with

the following alterations: Upon cell fixation and the freeze/thawing cycles,

cells were prepared for immunofluorescence as defined above. GFP-Mis18α

was detected by immunofluorescence as GFP signal is lost during FISH

fixation procedure. GFP-Booster (Chromotek), CENP-T (Barnhart et al,

2011) and anti-rabbit Dy680 (Rockland Immunochemicals) were used in a

dilution of 1:100, 1:1000, and 1:50, respectively. Subsequently, cells where

fixed with 2% formaldehyde for 10 minutes at room temperature and

washed with PBS. FISH protocol was then continued as described (Black et

al, 2007a). A chromosome 4q21.3 specific probe was generated by labeling a

mixture of BAC clones (RP11-113G13, RP11-204I22, RP11-209G6, RP11-

458J15; BACPAC Resources Center, Oakland, CA) with either Tetramethyl-

Rhodamine-5-dUTP or Fluorescein-12-dUTP (Roche, Indianapolis, IN), to

detect co-localization with GFP-Mis18α or with CENP-A-SNAP, respectively.

Coverslips were washed in 2X SSC (0.3 M NaCl, 30 mM Sodium Citrate, pH

7.0), containing 60% formamide prior to DAPI staining and mounting.

Microscopy

Cells were imaged on a DeltaVision Core system (Applied Precision)

controlling an inverted microscope (Olympus, IX-71), which is coupled to a

Cascade2 EMCCD camera (Photometrics). Images were collected at 1x

binning using a 100x oil objective (NA 1.40, UPlanSApo) with 0.2 mm Z-

sections scanning the entire nucleus. Images were subsequently deconvolved

using soft-WoRx (Applied Precision). Unless otherwise indicated, maximum

intensity projections of deconvolved images are shown. Centromere

quantification was performed using a custom made macro for ImageJ

(NIH), called CRaQ (Bodor et al, 2012). For quantitative purposes, images

Chapter 3

150

were collected on a 512x512 pixel chip and flatfield and camera noise

corrected during acquisition using soft-WoRx (Applied Precision).

Fluorescence quantification was performed on non-deconvolved images. For

centromere quantification, CRaQ was set to measure peak intensity values

within a 7x7 pixel box around the centroid position of the centromere. For

non-centromeric values (Figure 3.3D), a 2x2 pixel box was placed at a

position shifted away from the centromere centroid by 5 pixels in both x and

y. In Figure 3.3D, to enable the measurement of diffuse nuclear signals,

fluorescence immediately outside nuclei was used for background

correction. For Figure 3.4E, centromeric fluorescence was corrected for local

background for each centromere. To quantify the rate of division of SNAP-

tagged cells, we seeded one additional coverslip of CENP-A-SNAP cells for

each time point, and treated it identically to the other cells throughout the

duration of the experiment (TMR-Star and BTP were omitted and cells were

mock treated with DMSO instead). At the time of fixation, the extra

coverslip was trypsinized and cells were counted in a haemocytometer. To

calculate histone half-life we measured fluorescence intensities as a function

of number of cell divisions at 24, 48, and 72 hours. From this, we calculated

the best fit one phase decay regression line (F = e-k·t; where F is fluorescence

and t is time or number of divisions) using GraphPad Prism software (with a

constrained plateau at 0 and F0 = 1). Half-life equals ln(2)/k (Figure 3.3C).


151

REFERENCES

Ahmad K & Henikoff S (2002) Histone H3 variants specify modes of chromatin assembly. Proc. Natl. Acad. Sci. U. S. A. 99: 16477–16484




Bassett EA, Wood S, Salimian KJ, Ajith S, Foltz DR & Black BE (2010) Epigenetic centromere specification directs aurora B accumulation but is insufficient to efficiently correct mitotic errors. J. Cell Biol. 190: 177–185





Blower MD, Sullivan BA & Karpen GH (2002) Conserved organization of centromeric chromatin in flies and humans. Dev. Cell 2: 319–330


Burns JC, Friedmann T, Driever W, Burrascano M & Yee JK (1993) Vesicular stomatitis virus G glycoprotein pseudotyped retroviral vectors: concentration to very high titer and efficient gene transfer into mammalian and nonmammalian cells. Proc. Natl. Acad. Sci. U. S. A. 90: 8033–8037



Chapter 3

152







Gardner KE, Allis CD & Strahl BD (2011) OPERating ON Chromatin, a Colorful Language where Context Matters. J. Mol. Biol. 409: 36–46



Hu H, Liu Y, Wang M, Fang J, Huang H, Yang N, Li Y, Wang J, Yao X, Shi Y, Li G & Xu R-M (2011) Structure of a CENP-A-histone H4 heterodimer in complex with chaperone HJURP. Genes Dev. 25: 901–906


Keppler A, Gendreizig S, Gronemeyer T, Pick H, Vogel H & Johnsson K (2003) A general method for the covalent labeling of fusion proteins with small molecules in vivo. Nat. Biotechnol. 21: 86–89

Keppler A, Pick H, Arrivoli C, Vogel H & Johnsson K (2004) Labeling of fusion proteins with synthetic fluorophores in live cells. Proc. Natl. Acad. Sci. U. S. A. 101: 9955–9959


Lipsick JS (1996) One billion years of Myb. Oncogene 13: 223–235



153



Marzluff WF & Duronio RJ (2002) Histone mRNA expression: multiple levels of cell cycle regulation and important developmental consequences. Curr. Opin. Cell Biol. 14: 692–699

Mellone BG, Grive KJ, Shteyn V, Bowers SR, Oderberg I & Karpen GH (2011) Assembly of Drosophila centromeric chromatin proteins during mitosis. PLoS Genet. 7: e1002068


Moree B, Meyer CB, Fuller CJ & Straight AF (2011) CENP-C recruits M18BP1 to centromeres to promote CENP-A chromatin assembly. J. Cell Biol. 194: 855–871

Morgenstern JP & Land H (1990) Advanced mammalian gene transfer: high titre retroviral vectors with multiple drug selection markers and a complementary helper-free packaging cell line. Nucleic Acids Res. 18: 3587 –3596


Pearson CG, Yeh E, Gardner M, Odde D, Salmon ED & Bloom K (2004) Stable Kinetochore-Microtubule Attachment Constrains Centromere Positioning in Metaphase. Curr. Biol. 14: 1962–1967


Ray-Gallet D, Woolfe A, Vassias I, Pellentz C, Lacoste N, Puri A, Schultz DC, Pchelintsev NA, Adams PD, Jansen LET & Almouzni G (2011) Dynamics of histone H3 deposition in vivo reveal a nucleosome gap-filling mechanism for H3.3 to maintain chromatin integrity. Mol. Cell 44: 928–941





Chapter 3

154

Talbert PB & Henikoff S (2010) Histone variants — ancient wrap artists of the epigenome. Nat. Rev. Mol. Cell Biol. 11: 264–275


Xu M, Long C, Chen X, Huang C, Chen S & Zhu B (2010) Partitioning of histone H3-H4 tetramers during DNA replication-dependent chromatin assembly. Science 328: 94–98


Yuen KWY, Nabeshima K, Oegema K & Desai A (2011) Rapid de novo centromere formation occurs independently of heterochromatin protein 1 in C. elegans embryos. Curr. Biol. CB 21: 1800–1807


All experiments and analyses were performed by me, with the following

exceptions: LPV performed and analyzed experiments shown in Figure 3.6;

JFM performed experiment shown in Figure 3.S1; BEB created the

H3CATD-SNAP cell line; LETJ performed experiments shown in Figure 3.1

and 3.S2. The manuscript for this chapter was drafted and revised with help

of LETJ and constructive suggestions by all authors.

Acknowledgements

We are indebted to Don W. Cleveland who hosted preliminary

experiments in his laboratory. We thank Mariluz Gómez Rodríguez for help

with the IF-FISH procedure and Nuno Moreno for help with image

quantification. DLB and LPV are supported by the Fundação para a Ciência

e a Tecnologia (FCT) fellowships SFRH/BD/74284/2010 and

SFRH/BPD/69115/2010, respectively. This work is supported by NIH grant

GM082989, a Career Award in the Biomedical Sciences from the Burroughs

Wellcome Fund, and a Rita Allen Foundation Scholar Award to BEB and by

the Fundação Calouste Gulbenkian, FCT grants BIA-BCM/100557/2008,

BIAPRO/100537/2008, the European Commission FP7 programme and an

EMBO installation grant to LETJ.


155

SUPPLEMENTARY FIGURES

Figure 3.S1 (related to Figure 3.1) Direct pulse labeling of SNAP-tagged histones. (A) Outline of SNAP-based pulse

labeling experiment to visualize the total pool of SNAP protein. (B) Results of A for indicated histone-SNAP fusion

proteins. (C) Centromeric enrichment can be observed in cells expressing low levels of H4-YFP.

Chapter 3

156

Figure 3.S2 (related to Figure 3.2) Quench-chase-pulse experiments reveal distinct assembly modes for H4 during the

cell cycle. (A–E) Outlines and results for synchronized quench-chase-pulse experiments, analyzing H4-SNAP assembly

for indicated portions of the cell cycle. (F) As in E, except that nocodazole was added to arrest cells upon mitotic entry.


157

Figure 3.S3 (related to Figures 3 and 4) Stable retention at centromeres is restricted to CENP-A, H4, and H3CATD.

(A) Indicated cell lines were treated as in Figure 3.3A and imaged at indicated time points. Enlargements show rescaled

images of centromeric signal. (B) Results of experiment as in Figure 3.3A for SNAP-tagged H3.1, H3.3, and H2B.

Saturated enlargements of boxed cells are shown. No preferential retention at centromeres is observed for these

histones.


158

Appendix 3.1: The Role of CENP-C in CENP-A

Dynamics

Ana Filipa David, Dani L. Bodor, and Lars E.T. Jansen

Instituto Gulbenkian de Ciência, 2780-156, Oeiras, Portugal

NB: While the original conception and design of the experiments described here are

my own, the specific strategy was developed together with, and all experiments were

performed by, Ana Filipa David, a former MSc student working under my

supervision.

RESULTS

CENP-C is a member of the constitutive centromere associated network

(CCAN). This protein has been shown to directly bind to CENP-A

nucleosomes through its 6 terminal residues, LEEGLG (Carroll et al, 2010;

Guse et al, 2011; Kato et al, 2013). In addition, CENP-C is required for

recruitment of a large proportion of other CCAN members as well as the

mitotic kinetochore complex (Carroll et al, 2010; Gascoigne et al, 2011; Guse

et al, 2011; Przewloka et al, 2011; Screpanti et al, 2011) and can be sufficient

to recruit CENP-A in de novo centromere formation (Hori et al, 2013).

Indeed, depletion of CENP-C from human cells has been shown to lead to a

reduction of centromeric CENP-A levels (Carroll et al, 2010). However, it

remains unclear whether this results from a defect in assembly or retention

of CENP-A.

We combined RNAi mediated protein depletion of CENP-C with quench-

chase-pulse and pulse-chase experiments to analyze the effect on nascent

and pre-incorporated CENP-A, respectively. We found that the new pool of

CENP-A-SNAP is significantly reduced (p < 0.01) after CENP-C depletion as

compared to a control depletion (Figure 3.A, dark grey). In addition, we

The role of CENP-C in CENP-A dynamics

159

observed a small, yet non-statistically significant (p = 0.17) reduction of the

old pool of CENP-A-SNAP (Figure 3.A, light grey). Our preliminary results

indicate that CENP-C is involved in CENP-A assembly. In addition, it may

have an independent role in the maintenance of centromeric CENP-A

nucleosomes.

MATERIAL & METHODS

Cell culture

Experiments were performed on monoclonal HeLa cells, stably

expressing CENP-A-SNAP; clone #72 (Jansen et al, 2007). HEK-293-T cells

were used for production of lentiviral shRNA coding vectors (see below).

Cell culture conditions are identical to those described in chapter 3.

RNAi mediated protein depletion

A lentiviral-based system (Addgene) was used to deliver shRNA-coding

vectors into HeLa cells. HEK-293-T cells were co-transfected with shRNA-

coding plasmids (pLKO.1) and the packaging plasmids psPAX2 and

pMD2.G, using the Lipofectamine LTX according to manufacturer’s protocol

(Invitrogen). Transfection media was removed at 24h post-transfection and

replaced with fresh culture medium. Viral particles in suspension were

harvested after 24 hours and filtered through a 0.45μm filter.

Figure 3.A Depletion of CENP-C leads to a

reduction of both old and new pools of CENP-A,

as measured after quench-chase-pulse and pulse-

chase labeling of CENP-A-SNAP, respectively.

Average ± SEM of 4 independent replicate

experiments are shown; ~40–60 cells were

analyzed per experiment. Dashed line indicates

the normalized signal after scrambled control

depletion.


160

pLKO.1 plasmids with RNAi target sequences were purchased from

Addgene and target sequences are part of an algorithm-based shRNA library

(Moffat et al, 2006). The following targets were used for CENP-C depletion

(manufacturer’s references are indicated): TRCN0000148798,

TRCN0000150037, TRCN0000149366, TRCN0000148503, and

TRCN0000146581. The following sequence was used as a scrambled

control: CCTAAGGTTAAGTCGCCCTCG.

SNAP-labeling

CENP-A-SNAP cells were seeded in 24 wells plates and infected on the

next day with 70 μl of viral suspension of unknown titer in 2 ml of culture

medium containing 8 μg/mL polybrene. At 26 hours post-infection, cells

stably expressing shRNA were selected by addition of 1 μg/ml of puromycin.

For pulse-chase experiments, TMR-Star labeling was performed 24h post-

infection. For quench-chase-pulse experiments, BTP labeling was performed

40h post-infection and TMR-Star labeling 65h post-infection. In both cases,

cells were trypsinized and transferred to 8-well glass bottom chambers

(MatTek Corporation) at 67h post-infection and fixed at 72h post-infection.

SNAP labeling, fixation, DAPI labeling, and imaging were performed as

described in chapter 3. An automated algorithm was developed that

measures the maximum and median (equivalent to background) nuclear

TMR signal in maximum projected images and the difference between these

respective signals was used as a measure of signal intensity.

REFERENCES


Gascoigne KE, Takeuchi K, Suzuki A, Hori T, Fukagawa T & Cheeseman IM (2011) Induced ectopic kinetochore assembly bypasses the requirement for CENP-A nucleosomes. Cell 145: 410–422


The role of CENP-C in CENP-A dynamics

161



Kato H, Jiang J, Zhou B-R, Rozendaal M, Feng H, Ghirlando R, Xiao TS, Straight AF & Bai Y (2013) A Conserved Mechanism for Centromeric Nucleosome Recognition by Centromere Protein CENP-C. Science 340: 1110–1113

Moffat J, Grueneberg DA, Yang X, Kim SY, Kloepfer AM, Hinkle G, Piqani B, Eisenhaure TM, et al (2006) A lentiviral RNAi library for human and mouse genes applied to an arrayed viral high-content screen. Cell 124: 1283–1298

Przewloka MR, Venkei Z, Bolanos-Garcia VM, Debski J, Dadlez M & Glover DM (2011) CENP-C Is a Structural Platform for Kinetochore Assembly. Curr. Biol. 21: 399–405

Screpanti E, De Antoni A, Alushin GM, Petrovic A, Melis T, Nogales E & Musacchio A (2011) Direct Binding of Cenp-C to the Mis12 Complex Joins the Inner and Outer Kinetochore. Curr. Biol. 21: 391–398

CHAPTER 4

The Quantitative Architecture of Centromeric

Chromatin

Dani L. Bodor1, João F. Mata1, Mikhail Sergeev2, Ana Filipa David1, Kevan J.

Salimian3, Tanya Panchenko3, Don W. Cleveland4, Ben E. Black3, Jagesh V. Shah2,

and Lars E.T. Jansen1

1 Instituto Gulbenkian de Ciência, 2780-156, Oeiras, Portugal.

2 Harvard Medical School, Boston MA 02115, USA.

3 University of Pennsylvania, Philadelphia, PA 19104-6059, USA.

4 Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA.

NB: This chapter is a near literal transcription of eLife 2014;3:e02137. Noteworthy

is the change of the term “mass action mechanism” with the more appropriate

“mass action-like mechanism” throughout the chapter (see Chapter 5).

ABSTRACT

The centromere, responsible for chromosome segregation during

mitosis, is epigenetically defined by CENP-A containing nucleosomes. The

amount of centromeric CENP-A has direct implications for both the

architecture and epigenetic inheritance of centromeres. Using

complementary strategies, we determined that typical human centromeres

contain ~400 molecules of CENP-A, which is controlled by a mass action-

like mechanism. This number, despite representing only ~4% of all

centromeric nucleosomes, forms a ~50-fold enrichment to the overall

genome. In addition, although pre-assembled CENP-A is randomly

segregated during cell division, this amount of CENP-A is sufficient to

prevent stochastic loss of centromere function and identity. Finally, we

produced a statistical map of CENP-A occupancy at a human neocentromere

and identified nucleosome positions that feature CENP-A in a majority of

cells. In summary, we present a quantitative view of the centromere that

provides a mechanistic framework for both robust epigenetic inheritance of

centromeres and the paucity of neocentromere formation.

Counting CENP-A molecules in human cells

165

INTRODUCTION

Centromeres are essential for proper cell division. During mitosis, a

transient structure called the kinetochore is assembled onto centromeric

chromatin, which mediates the interaction between DNA and the mitotic

spindle (Allshire & Karpen 2008; Cheeseman & Desai 2008). Intriguingly,

although centromeres are directly embedded in chromatin, specific DNA

sequences are neither necessary nor sufficient for centromere function. This

is best exemplified by the rare occurrence, within the human population, of

neocentromeres: functional centromeres that have repositioned to atypical

loci on the chromosome (Amor et al., 2004; Marshall et al., 2008; du Sart et

al., 1997; Voullaire et al., 1993). Rather than centromeric sequences, the

primary candidate for epigenetic specification of centromeres is the histone

variant CENP-A, which replaces canonical H3 in centromeric nucleosomes

(Henikoff et al., 2000; Palmer et al., 1987, 1991; Stoler et al., 1995; Yoda et

al., 2000). CENP-A chromatin is sufficient for recruitment of the

downstream centromere and kinetochore complexes (Barnhart et al., 2011;

Carroll et al., 2009, 2010; Foltz et al., 2006; Guse et al., 2011; Mendiburo et

al., 2011; Okada et al., 2006). In addition, CENP-A is stably transmitted at

centromeres during mitotic (Bodor et al. 2013; Jansen et al. 2007) and

meiotic (Raychaudhuri et al., 2012) divisions, and its assembly is tightly cell

cycle controlled (Jansen et al., 2007; Schuh et al., 2007; Silva et al., 2012).

Importantly, targeting of this protein to an ectopic site of the genome is

sufficient to initiate an epigenetic feedback loop, recruiting more CENP-A to

this site (Mendiburo et al. 2011). However, little is known about the quantity

of CENP-A present at centromeres, despite this being an essential parameter

for a functional understanding of both centromeric architecture and

epigenetic inheritance. Here, we use multiple, independent approaches to

determine the absolute copy number of CENP-A at centromeres. In

addition, we provide novel insights in the mechanisms of centromere size

control.

Chapter 4

166

RESULTS

Modification of endogenous CENP-A alleles in diploid human

cells

To determine absolute centromeric CENP-A levels in human cells we set

out to build cell lines in which the entire CENP-A pool is fluorescent. To

accomplish this, we removed a significant and essential portion of the

CENP-A gene to create a knock-out allele in stably diploid retinal pigment

epithelium (RPE) cells (Figure 4.1A, bottom). Subsequently, a fluorescent

knock-in allele was created by placing GFP or YFP encoding sequences in

frame with the sole remaining CENP-A gene (Figure 4.1A, middle).

Specifically, we have built the following endogenously targeted RPE cell

lines: CA+/-, CAG/-, CAY/-, and CA+/F [where + = wildtype; − = knock-out; G =

GFP knock-in; Y = YFP knock-in; F = floxed (to control for potential gene-

targeting artifacts); Figure 4.1-S1A]. Western blot analysis confirms that

CAG/- and CAY/- cells exclusively contain tagged CENP-A (of ~43 kDa), while

CA+/+ (wildtype), CA+/F, and CA+/- cells only express wildtype CENP-A (~16

kDa) protein (Figure 4.1B). Importantly, heterozygous expression or tagging

of endogenous loci did not interfere with cell viability.

Figure 4.1 (next page) CENP-A levels are regulated by a mass action-like mechanism. (A) Schematic of gene-

targeting strategy that allowed for the creation of CENP-A knockout and fluorescent knock-in alleles. The region

encoding the essential CENP-A targeting domain [CATD (Black et al. 2007)] is indicated. (B) Quantitative immunoblots

of CENP-A, HJURP, and Mis18BP1 in differentially targeted RPE cell lines. α-tubulin is used as a loading control. (C)

Immunofluorescence images of same cell lines as in B. CENP-A intensity is represented in a heat map as indicated on

the right. The fold difference ± SEM (n is biological replicates) compared to wildtype RPE cells is indicated below. Scale

bar: 10 μm. Note that, in contrast to quantification of immunoblots, immunofluoresce detection of untagged and tagged

CENP-A is directly comparable. (D) Quantification of centromeric CENP-A levels (from C) by immunofluorescence (IF)

and total CENP-A levels (n = 4–9 independent experiments as in B) by western blot (WB). All cell lines expressing

untagged CENP-A are normalized to CA+/+ while those expressing tagged CENP-A are normalized to the centromeric

CAY/- levels measured in c, as indicated by dashed lines. (E) Correlation of centromeric and total cellular CENP-A levels

as measured in D. Dashed line represents a predicted directly proportional relationship with indicated correlation

coefficients. Throughout, the average ± SEM is indicated. (F) Quantification of centromeric CENP-A levels in

synchronized HeLa cells (based on anti-CENP-A staining) within a single cell cycle after transient transfection of

indicated proteins. Asterisk indicates statistically significant increase compared to control or indicated transfections

(one-tailed t-test; p<0.05; n = 3); NS indicates no significant increase. Average ± SEM of three independent

experiments is shown.


167

Chapter 4

168

Centromeric CENP-A levels are regulated by a mass action-like

mechanism.

While CENP-A is an essential and constitutive component of centro-

meres, how the size of the centromeric chromatin domain is controlled is not

known. We analyzed the consequence of different CENP-A expression levels

in the aforementioned RPE cell lines, as well as in a cells that ectopically

overexpressed CENP-A-YFP (CAY/-+OE; Figure 4.1B). First, we measured

the total protein pool of CENP-A by quantitative immunoblotting. While we

found the detection output for CENP-A to be linear over at least a 32-fold

range (Figure 4.2E), differences in protein transfer efficiencies do not allow

for a comparison between proteins of different sizes, e.g. (GFP- or YFP-)

tagged and untagged (wildtype) CENP-A (Figure 4.2—S3). Nevertheless, we

could directly compare CAG/-, CAY/-, and CAY/-+OE cell lines and found that

cellular CENP-A content spans a 6-fold range (Figure 4.1B, D).

Given its essential role in centromere function, we predicted a tight

control of centromeric CENP-A levels. However, instead of maintaining a

fixed amount of CENP-A at centromeres, the levels varied extensively

(Figure 4.1C). Both CA+/- and CAG/- cells, which contain a single intact allele,

have decreased centromeric CENP-A levels, while the parental CA+/F cells

maintain wildtype levels. Surprisingly, despite expressing CENP-A from a

single allele, CAY/- cells have increased CENP-A levels, which may be due to

adaptations that arose during the creation of this cell line. As expected,

CENP-A levels are further elevated in CAY/-+OE cells (Figure 4.1C).

Remarkably, we found a very high correlation (r2 = 84%) for a hypothetical

directly proportional relationship between centromeric and total cellular

CENP-A-GFP or -YFP levels (Figure 4.1D, E). Similarly, despite an only

~twofold range of expression, we still observe a high correlation with direct

proportionality (r2 = 71%) for cells expressing untagged CENP-A (Figure

4.1D, E). Thus, our observations indicate that centromeric levels are

determined by a mass action-like mechanism, where the amount of

centromeric CENP-A varies in direct proportion with the cellular content.


169

An alternative hypothesis is that stable cell lines have undergone long-

term adaptation to altered CENP-A expression, which has led to re-

equilibrated centromeric levels. For example, proteins involved in CENP-A

deposition at the centromere may have adapted to CENP-A expression

levels. Indeed, we see a weak correlation between the levels of CENP-A and

its histone chaperone HJURP (Barnhart et al. 2011; Dunleavy et al. 2009;

Foltz et al. 2009) in our cells lines (Figure 4.1B, 4.1—S1B). Conversely, no

correlation was detected for Mis18BP1 (Figure 4.1B, 4.1—S1C), another

essential protein for CENP-A assembly (Fujita et al. 2007; Maddox et al.

2007), arguing that it is a non-stoichiometric component of the loading

pathway. To test for long-term adaptation effects, we analyzed the

consequence of CENP-A and/or HJURP overexpression in a single round of

CENP-A assembly. Therefore, we transiently expressed CENP-A and/or

HJURP and measured the level of centromeric CENP-A after one division in

HeLa cells, which can be effectively synchronized in S phase using

thymidine. While induction of CENP-A leads to a prompt increase in

centromeric levels, no (additional) effect was observed by expression of

HJURP (Figure 4.1F). Together, our results strongly suggest that centro-

meric CENP-A levels are directly regulated by its protein expression levels.

Centromeres contain ~400 molecules of CENP-A.

To understand how CENP-A chromatin is self-propagated and nucleates

the kinetochore, it is critical to establish the absolute amount of CENP-A

present. In vertebrates, previous estimates range from a few tens of

molecules [in chicken DT40 cells (Ribeiro et al. 2010)] to a potential

maximum of tens of thousands [in HeLa cells (Black et al. 2007)]. To

directly determine the copy number of CENP-A on human centromeres, we

developed a 3D imaging strategy (Figure 4.2A), which was adapted from a

method used to quantify cytokinesis proteins in fission yeast (Wu & Pollard

2005; Wu et al. 2008). In brief, we use a non-cell permeable dye (Figure

4.2A, I) to determine the 3D shape of cells (Figure 4.2A, II) and measure the

Chapter 4

170

total fluorescence within the entire cell volume (Figure 4.2A, III). Total

cellular fluorescence of CAY/- cells (Figure 4.2A, III) was corrected for

autofluorescence of wildtype RPEs (Figure 4.2A, IV), resulting in a measure

of total YFP-derived signal. Next, centromere specific fluorescence was

measured after correction for local background [Figure 4.2A, V; (Hoffman et

al., 2001)] and axial oversampling. Importantly, fluorescence lifetime of

CENP-A-YFP is similar between highly concentrated centromeric and

diffuse cytoplasmic pools (Figure 4.2—S1), arguing that clustering does not

lead to changes in fluorescence efficiency. In effect, our 3D integrated

fluorescence strategy measures the fraction of centromeric-to-total CENP-A.

We find that while CENP-A is enriched at centromeres, on average only

0.44% of cellular CENP-A is present per centromere in CAY/- cells (Figure

4.2B). Very similar fractions were observed in CAG/- and CAY/-+OE cells

(0.38% in both cases; Figure 4.2C, 4.2-S2A, B), which provides an additional

line of evidence in support of a mass action-like mechanism for CENP-A

assembly. Furthermore, these findings show that a surprising minority,

about one-fifth of the CENP-A protein content (0.44% x 46) is present on

the functionally relevant subcellular location, i.e. at the centromeres.

To convert centromeric fractions to absolute amounts, we determined

the total number of CENP-A molecules in RPE cells. We prepared whole cell

extracts of RPE cells and analyzed these alongside highly purified

recombinant CENP-A/H4-complexes of known concentration by

quantitative immunoblotting (Figure 4.2D). Importantly, we ensured that

Figure 4.2 (next page) Human centromeres contain 400 molecules of CENP-A. (A) Schematic outline of strategy

allowing for the quantification of the centromeric fraction of CENP-A compared to the total cellular pool. Scale bars: 5

μm. (B) Quantification of the centromeric fraction of CENP-A in CAY/- cells. Each circle represents one centromere;

circles on the same column are individual centromeres from the same cell. Dashed line indicates average of all

centromeres. (C) Quantification of the centromeric fraction of CENP-A in indicated cell lines. Each square represents the

average centromeric signal from one cell; squares on the same column are individual cells from the same experiment

(Exp). Figure 4.2-S2 shows quantification of individual centromeres in CAG/- and CAY/-+OE cells. (D) Representative

quantitative immunoblot of purified recombinant CENP-A and endogenous CENP-A from whole cell extracts (WCE). (E)

Quantification of D. Solid line represents the best fit linear regression. Dashed line represents the amount of CENP-A

from 150,000 cells. (F) Quantification of total cellular CENP-A copy number. Each diamond represents one replicate

experiment; measurement from E is indicated as a grey diamond. (G) Calculation of average CENP-A copy number per

centromere (CEN) in wildtype RPE cells. Throughout, the average ± SEM is indicated.


171

Chapter 4

172

recombinant and cellular CENP-A have the same transfer efficiency and can

be directly compared to each other (Figure 4.2—S3). Fitting the cellular

amount of CENP-A onto a linear regression curve of purified protein (Figure

4.2E) shows that CA+/+ cells contain an average of ~9.1 ± 1.1·104 (n = 10)

molecules of CENP-A per cell (Figure 4.2F). Because the centromeric

fraction of CENP-A is fixed, we can calculate the absolute amount of

CENP-A per centromere (Figure 4.2G, 4.2—S2c) and show that wildtype

RPE cells contain ~400 molecules of CENP-A on an average centromere.

Both the expression and centromeric loading of CENP-A are cell cycle

regulated (Figure 4.3A). In human cells, cellular protein levels of CENP-A

peak in late G2 (Shelby et al., 2000), while centromere assembly occurs in

early G1 phase (Jansen et al., 2007). Thus it is possible that part of the cell-

to-cell variation of the centromeric CENP-A ratio observed in Figure 4.2C is

due to differing cell cycle stages. We tested this by using the previously

developed fluorescent ubiquitin-based cell cycle indicator (FUCCI), which

can be used in live cells (Sakaue-Sawano et al., 2008). In particular, we used

hCdt1(30/120)-RFP, which is expressed ubiquitously throughout the cell

cycle, but specifically degraded in S, G2, and M phases (Sakaue-Sawano et

al., 2008). As a result, protein levels increase as cells enter and progress

through G1 phase, peak at the G1/S boundary, and then drop until cells re-

enter G1 (Figure 4.3A). We expressed this protein in CAY/- cells and tracked

the RFP signal intensity over time (Figure 4.3B, 4.3-S1A) to identify cells

that entered S phase (see methods for details). We compared their ratio of

centromeric-to-total CENP-A to randomly cycling cells and found that

neither the mean nor the variance differs significantly between these two

populations of cells (Figure 4.3C). Importantly, expression of the FUCCI

marker itself has no effect on the measurements performed (Figure 4.3—

S1B). While the centromeric fraction of CENP-A is likely low in G2 phase

and high just after assembly in early G1, we find that the variation observed

in Figure 4.2C is not a consequence of such cell cycle induced effects and

may instead reflect inherent variation between cells.


173

Figure 4.3 Centromeric CENP-A levels are equivalent between S phase and randomly cycling cells. (A) Cartoon

depicting changes in cell morphology and nuclear levels of hCdt1(30/120)-RFP (in red) throughout the cell cycle

(Sakaue-Sawano et al., 2008). Approximate timing of CENP-A expression (Shelby et al., 2000) and centromeric loading

(Jansen et al., 2007) are indicated in orange and blue, respectively. The stage at which cells were analyzed to measure

the centromeric fraction of CENP-A is indicated in green. (B) An example trace of a cell entering S phase (indicated by a

sudden decrease in RFP levels) is shown. The centromeric fraction of CENP-A was measured at this point as outlined in

Figure 4.2A. Peak expression is normalized to 100 and background fluorescence to 0. Micrographs of hCdt-1(30/120)-

RFP at indicated timepoints are shown below. (C) As in Figure 4.2C. Orange squares represent cells that have passed

the G1-S transition point, as indicated by decreasing levels of hCdt-1(30/120)-RFP. Grey squares represent randomly

cycling cells. No statistically significant differences (NS) were observed between randomly cycling cells and S phase cells.

Although the method we employed to measure centromeric ratios is

internally controlled, it relies on measurement of integrated fluorescence of

whole cells, including highly dilute cytoplasmic CENP-A. To exclude

potential errors in measurements of low protein concentration, we stably

expressed H2B-RFP in CAY/- cells (Figure 4.4A, inset) and determined that

0.73% of nuclear CENP-A is present on each centromere (Figure 4.4A). In

Chapter 4

174

addition, low salt fractionation experiments indicate that ~74% of cellular

CENP-A co-pellets with other chromatin components in CAY/-+H2B-RFP

cells (Figure 4.4B), indicating that this represents the stable nuclear pool.

Combined, we find a similar number of CENP-A molecules per centromere

when analyzing the nuclear pool (492 molecules; Figure 4.4C) as when

measuring total cellular CENP-A. This argues that the measurements

performed above are not significantly influenced by a potential inaccuracy in

determining the cytoplasmic pool. Interestingly, it has recently been shown

that detectable levels of CENP-A are assembled into non-centromeric

chromatin of HeLa cells (Lacoste et al., 2014). Indeed, we now find that, at

least in RPE cells the proporation of chromatin bound CENP-A outside of

the centromere is surprisingly high (~66% in this cell line).

Figure 4.4 Measurement of nuclear CENP-A confirms centromeric copy number. (A) As in Figure 4.2B, except that the

centromeric fraction compared to total nuclear pool is indicated. Inset shows a representative image of a CAY/-+H2B-

RFP cell (scale bar: 2.5 μm). (B) Quantitative immunoblot showing the soluble fraction and a dilution series from the

insoluble fraction of CENP-A-YFP in CAY/-+H2B-RFP cells (left). Tubulin is used as marker for the soluble fraction and

H4K20me2 [exclusively found in chromatin (Karachentsev et al. 2007)] for the insoluble fraction. Quantification of

insoluble fraction of CENP-A is shown to the right. (C) Calculation of the average CENP-A copy number per centromere

(CEN) in wildtype RPE cells, based on results from CAY/-+H2B-RFP cells.


175

CENP-A copy number confirmed by three independent methods.

To further validate the strategy for measuring CENP-A copy numbers, we

used two additional independent quantification methods. First, we applied a

method that employs the statistical properties of fluorescence redistribution

(Rosenfeld et al., 2005, 2006). This method relies on the fact that random

segregation leads to each daughter receiving an (unequal) fraction of

molecules, where the distribution of differences relates to the total number

of molecules (as outlined in Figure 4.5A). During mitosis, sister centromeres

form individually resolved spots by light microscopy, allowing us to measure

the fluorescence intensity of individual sisters (Figure 4.5B). We find that

rather than accurately segregating exactly half of pre-assembled CENP-A

onto each daughter chromatid, the difference between sister centromeres

follows a random distribution (Figure 4.5B, C). Previously, Rosenfeld et al.

(2005, 2006) have provided mathematical evidence that measurements of

this deviation allow for the determination of the fluorescence intensity of a

single heritable, segregating unit (Figure 4.5A). We measured an average of

75.4 segregating units of CENP-A-GFP per centromere in CAG/- cells (Figure

4.5D). Because each segregating unit consists of one or more nucleosomes,

containing 2 molecules of CENP-A each (Bassett et al. 2012; Hasson et al.

2013; Sekulic et al. 2010; Tachiwana et al. 2011; Padeganeh et al. 2013), an

average CAG/- centromere has a minimum of 150.8 molecules of CENP-A.

Correcting the amount of CENP-A measured in CAG/- cells for wildtype levels

(Figure 4.1C) results in ≥377 molecules of CENP-A per centromere (Figure

4.5D, right y-axis). Importantly, these measurements differ significantly if

random centromere pairs are chosen for which no statistical correlation

exists (Figure 4.5—S1E). This confirms that fluorescence intensities at sister

centromeres co-vary and renders this type of analysis suitable for centro-

mere quantification. Stochastic fluctuation measurements in CAY/- and CAY/-

+OE cells indicates that wildtype cells contain ≥188 and ≥149 CENP-A

molecules per centromere, respectively (Figure 4.5—S1A–D). Importantly,

the number of co-segregating CENP-A nucleosomes is unknown, which can

Chapter 4

176

be one or more. Therefore, despite the variation between the cell lines used

here, all results obtained from this method provide a minimum estimate of

the centromeric CENP-A copy number that is in agreement with the 400

centromeric molecules of CENP-A measured above (Figure 4.2G).

Next, we used a yeast strain that harbors a chromosomally integrated

4kb LacO-array and expresses GFP-LacI as a calibrated fluorescent standard

(Lawrimore et al. 2011). While there is a potential for 204 molecules of

GFP-LacI to be bound to this array (Lawrimore et al. 2011), it is unlikely that

the entire array is fully occupied at any moment. Because CAG/- cells express

the same version of GFP as this yeast strain, direct comparison of

fluorescent foci (Figure 4.5E) provides a maximum estimation of the

centromeric CENP-A-GFP copy number. In this way, we determined that

CAG/- centromeres contain at most 215 ± 32 CENP-A-GFP molecules, which

translates to ≤538 CENP-A molecules in wildtype cells (Figure 4.5F).

Importantly, the copy number that we measure directly by our 3D integrated

fluorescence approach is in close agreement with minimum and maximum

estimates of the stochastic fluctuation and fluorescent standard approaches,

respectively (Figure 4.5G). This provides confidence that 400 molecules of

CENP-A per centromere in wildtype RPE cells is an accurate measure.

Figure 4.5 (next page) Independent quantification methods confirm centromeric CENP-A copy number. (A)

Stochastic fluctuation method: Cartoon depicting inheritance and random redistribution of parental CENP-A

nucleosomes onto sister chromatids during DNA replication. A hypothetical distribution of the absolute difference

between the two sister centromeres, as well as the formula for calculating the fluorescence intensity per segregating unit

(α) are indicated on the right. (B) Representative image of mitotic CENP-A-YFP expressing cell. CENP-B staining allows

for identification of sister centromeres. Blowup to the right represents a single slice of the boxed region showing that

CENP-B is located in between the CENP-A spots of sister centromeres. (C) Frequency distribution of the difference

between CENP-A-GFP intensity of sister centromeres in CAG/- cells. (D) Quantification of centromeric CENP-A-GFP

based on the stochastic fluctuation method. Each circle represents one centromere; circles on the same column are

individual centromeres from the same cell. Left y-axis indicates segregating CENP-A-GFP units in CAG/- cells; right y-

axis shows the conversion to minimum number of centromeric CENP-A molecules in CA+/+ (WT) cells. (E) Fluorescent

standard method: Representative fluorescence images of 4kb-LacO, LacI-GFP S. cerevisiae and human CAG/- cells. (F)

Quantification of fluorescence signals of LacI-GFP and CENP-A-GFP spots (n = 2 biological replicates). The left y-axis

indicates the fluorescence intensity normalized to LacI-GFP; the right y-axis shows the conversion to maximum number

of centromeric CENP-A molecules in wildtype cells. (G) Comparison of independent measurements for the centromeric

CENP-A copy number [corrected for CA+/+ levels; Stoch. fluctuations = stochastic fluctuation method (Figure 4.5A);

Integr. fluorescence = integrated fluorescence method (Figure 4.2A)]. Levels from all strategies are corrected for CA+/+

(WT) levels. Throughout, the average ± SEM and scale bars of 2.5 μm are indicated.


177

Chapter 4

178

Assessing the critical number of CENP-A nucleosomes.

While cells are able to survive with a 6-fold range of CENP-A levels

(Figure 4.1D), centromere function may be compromised when levels are

not accurately maintained. Indeed, based on a conserved ratio of centromere

and kinetochore proteins and kinetochore microtubules between multiple

yeast species as well as chicken DT40 cells, it has been hypothesized that

centromeres form modular structures by repeating individual structural

subunits (Joglekar et al., 2008; Johnston et al., 2010), as originally

proposed by Zinkowski et al (1991). Thus, the amount of CENP-A would

directly reflect the number of downstream centromere and kinetochore

proteins and microtubule attachment sites. Conversely, experiments in

human cells indicate that the centromere is assembled by multiple

independent subcomplexes (Foltz et al., 2006; Liu et al., 2006). Here, we

analyzed whether altering the levels of CENP-A has an effect on the

recruitment of other, downstream centromere or kinetochore proteins. Both

CENP-C and CENP-T rely on CENP-A for their centromeric recruitment

(Fachinetti et al. 2013; Liu et al. 2006; Régnier et al. 2005) and have

recently been shown to be responsible for mitotic recruitment of the KMN

network (Gascoigne et al. 2011), including the key microtubule binding

protein Hec1/NDC80 (Cheeseman et al. 2006; DeLuca et al. 2006).

Interestingly, we found that none of these three proteins were significantly

affected by altering the levels of CENP-A between 40% and 240% of

wildtype levels (Figure 4.6A, 4.6—S1). In line with previous findings

(Fachinetti et al. 2013; Liu et al. 2006), these results argue against a

modular centromere architecture where CENP-A nucleosomes form

individual binding sites for downstream components. Rather, a >2½ -fold

excess of CENP-A appears to be present for recruitment of centromere and

kinetochore complexes of fixed pool size.


179

Figure 4.6 Reduction of CENP-A leads to a CENP-C, CENP-T, and Hec1 independent increase in micronuclei. (A)

Quantification of centromeric CENP-A (from Figure 4.1), CENP-C, CENP-T, and Hec1 levels for indicated cell lines; n =

4 independent experiments in each case. Note that cell lines carrying tagged CENP-A have a slight, yet non-significant

impairment in recruiting CENP-C, CENP-T, and Hec1. However, this does not correlate with the CENP-A levels

themselves. Below, representative images of indicated antibody staining from CA+/+ cells are shown. Representative

images from all cell lines can be found in Figure 4.6—S1. (B) Quantification of the fraction of cells containing

micronuclei (MN) for indicated cell lines. Asterisk indicates statistically significant increase compared to wildtype

[paired t-test; p<0.05; n = 3–4 independent experiments (500–3000 cells per experiment per cell line)]; NS indicates

no significant difference. Throughout, the average ± SEM is indicated and dashed lines represent wildtype levels. Scale

bars: 5 μm.

Intriguingly, despite no quantitative effect on centromeric proteins, we

observed that decreasing CENP-A levels leads to an increase in the fraction

of cells containing micronuclei (MN; Figure 4.6B). MN often arise as a

consequence of mitotic errors, such as lagging chromosomes during

anaphase (Ford et al., 1988), breakage of anaphase bridges (Hoffelder et al.,

2004), or multipolar mitoses (Utani et al., 2010). The presence of MN can be

scored by DAPI staining (Figure 4.6B, bottom). MN are found in WT cells at

a baseline fraction of ~0.5% (Figure 4.6B). Both cell lines with decreased

CENP-A levels show a significantly increased fraction of cells with MN.

Importantly, these two cell lines were derived independently from the CA+/F

cell line (Figure 4.1—S1A), which has wildtype levels of CENP-A and no

Chapter 4

180

significant increase in MN (Figure 4.6). In addition, neither cell line with

increased CENP-A levels have a larger fraction of MN than CA+/F cells. While

the essential role for CENP-A in centromere function is well established

(Black et al., 2007; Liu et al., 2006; Régnier et al., 2005), our results

indicate that a critical level of CENP-A is passed after reducing the levels to

50%. However, the molecular mechanism responsible for MN formation

remains unclear, as downstream centromere and kinetochore components

of CENP-A remain unaffected.

The contribution of cell type and local centromere features to

centromeric CENP-A levels.

Interestingly, we find that not all centromeres of the same cell have equal

amounts of CENP-A (Figure 4.5D). This could either be due to in cis features

driving differential regulation of CENP-A on individual centromeres, or by

unbiased stochastic effects at centromeres. To distinguish between these

possibilities, we measured the centromeric levels of endogenous CENP-A on

specific chromosomes. First, we analyzed a monoclonal HCT-116 cell line

that has an integrated Lac-array in a unique position in the genome

(Thompson & Compton 2011). While the site of integration is unknown,

expressing LacI-GFP allows for the identification of the same chromosome

in a population of cells (Figure 4.7A). Both the average and variance of

CENP-A at this centromere does not differ statistically from the bulk (Figure

4.7B, 4.7—S1A), arguing against centromere specific features driving CENP-

A levels on the Lac-marked chromosome. Conversely, we found that the Y-

centromere, uniquely identified by the lack of CENP-B [Figure 4.7C;

(Earnshaw et al., 1987)], of two independent male cell lines had a slight yet

significant reduction of CENP-A (19% in wildtype HCT-116 and 13% in

DLD-1; Figure 4.7D, 4.7—S1B, C), consistent with an earlier report (Irvine et

al. 2004). Finally, we used a human patient derived fibroblast cell line

(PDNC-4) where one centromere of chromosome 4 has repositioned to an

atypical location (Amor et al. 2004), which we designate as NeoCEN-4


181

(Figure 4.7E). As has been observed in other cell lines derived from this

patient (Amor et al. 2004), we found that the NeoCEN-4 has a ~25%

decrease in centromeric CENP-A (Figure 4.7F 4.7—S1D). Taken together,

these results show that while CENP-A expression drives centromeric levels,

local sequence or chromatin features can also contribute to the average

amount of CENP-A at specific centromeres. Nevertheless, even on these

centromeres, the variance in CENP-A levels is maintained, indicating that

other stochastic processes contribute to CENP-A levels.

Next, to determine whether the CENP-A copy number of our model cell

line is representative for functionally different cells, we performed

comparative immunofluorescence against CENP-A (Figure 4.7G). We

analyzed four different cancer cell lines (HeLa, U2OS, HCT-116, and DLD-1),

as well as the PDNC-4 neocentromere cell line discussed above and primary

human fibroblasts that were cultured for a limited number of passages (<15)

since their isolation from a patient (Figure 4.7G). Using these cell lines, we

found a 6-fold range of centromeric CENP-A levels (Figure 4.7H), indicating

that there is substantial variance between different cell lines. However, we

find that the primary cells have a similar amount of CENP-A as RPEs

(Figure 4.7H), arguing that our measure of absolute CENP-A copy numbers

made in RPE cells is relevant for healthy, human tissues as well.

We combined these results with our measurements of individual

centromeres and determined that, while an average centromere in PDNC-4

cells contains ~579 molecules of CENP-A, the NeoCEN-4 only contains

~432. Average Y-centromeres contain ~143 or ~87 molecules in HCT-116

and DLD-1 cells, respectively (Figure 4.7J). In conclusion, we find evidence

that cis-elements can have an effect on CENP-A levels, at least on human Y-

and neocentromeres.

Chapter 4

182


183

Figure 4.7 (previous page) Centromere specific distribution of CENP-A. (A, C, E) Representative image of mitotic

spreads for LacI-GFP::LacO expressing HCT-116 cells (A); wildtype HCT-116 cells (C); and PDNC-4 cells (E). Blowups

show the chromosome containing the integrated Lac-array (A); the Y-chromosome (CENP-B negative; outlined) as well

as a CENP-B positive autosome (C); and the neocentric chromosome 4, containing 2 pairs of ACA spots (staining both

CENP-A and CENP-B), but only 1 pair of CENP-A spots (E). (B, D, F) Quantification of CENP-A levels on the

centromere of the chromosome containing the Lac-array [CEN-Lac; n = 29; (B)]; the Y-chromosome [CEN-Y; n = 18;

(D)]; and neocentric chromosome 4 [NeoCEN-4; n = 39; (F)] of indicated cell lines compared to all other centromeres

within the same cell (Other CENs; n = 1008, 620, and 1592, respectively). Median (line), interquartile distance (box), 3x

interquartile distance or extremes (whiskers), and outliers (spots) are indicated. Figure 4.7—S1 shows results of

individual centromeres. Asterisk indicates statistically significant difference (t-test; p<0.05); NS indicates no significant

difference. (G) Representative images of CENP-A antibody staining in indicated cell types; independent images of RPEs

are shown as reference. (H) Quantification of G. Mean ± SEM for n = 3–4 independent experiments is shown. Left y-

axis represents centromeric CENP-A levels normalized to RPE cells; right y-axis shows number of CENP-A molecules

per centromere (CEN). (J) Combined results from a-h allow for the determination of CENP-A copy numbers on

individual chromosomes. (K) Statistical map of the distribution of 216 CENP-A nucleosomes on the NeoCEN-4 at three

different scales. The top 216 peaks are indicated in blue. Y-axis indicates the probability of CENP-A occupancy for each

nucleosome. (L) Histogram of the CENP-A nucleosome occupancy. Inset shows the distribution of 216 neocentric

CENP-A nucleosomes on the 10% highest occupancy peaks (green) and 90% lowest occupancy peaks (red).

A statistical map of CENP-A at individual nucleosome positions.

The number of CENP-A nucleosomes we find at individual centromeres

is much smaller (~25-fold, see Figure 4.8A) than the total number of

nucleosome positions on human centromeric DNA. This indicates that either

CENP-A is randomly distributed at a low level throughout the centromere

domain or that it occupies specific “hotspots”. However, it is not possible to

map individual CENP-A nucleosomes on canonical centromeres, due to their

repetitive nature. However, a recent high-resolution ChIP-seq analysis of the

(non-repetitive) NeoCEN-4 identified 1113 unique CENP-A nucleosome

positions spanning a ~300 kb locus (Hasson et al. 2013). By combining the

relative height of individual peaks with the total number of CENP-A

nucleosomes at this neocentromere, we were able to determine the fraction

of cells containing CENP-A at each nucleosome position (Figure 4.7K). This

statistical map of CENP-A occupancy shows that, while the median is ~6%

(Figure 4.7L), individual positions feature CENP-A with a surprisingly high

occupancy (up to 80% of all cells; Figure 4.7K, arrow). Remarkably, more

than one third of all CENP-A nucleosomes are located on the top 10%

potential positions (Figure 4.7L, inset). This strongly suggests that, at least

on the NeoCEN-4, a number of nucleosome positioning sequences exist that

strongly favor CENP-A over other H3 variants.

Chapter 4

184

DISCUSSION

It has been proposed that centromeres in budding yeast feature a single

nucleosome of CENP-A (Furuyama & Biggins 2007; Meluh et al. 1998). For

this reason, yeast centromeres have been extensively used to calibrate

fluorescence intensities of CENP-A and other proteins from a number of

species (Joglekar et al., 2006, 2008; Johnston et al., 2010; Schittenhelm et

al., 2010). However, the single nucleosome hypothesis has recently been

challenged (Coffman et al., 2011; Haase et al., 2013; Lawrimore et al., 2011).

To avoid dependency on any single reference, we used three independent

methods to measure the human centromeric CENP-A copy number. One

strategy uses intrinsically controlled fluorescence ratios of cellular and

centromeric CENP-A-YFP signals (Figure 4.2A). The second method does

not rely directly on fluorescence intensities, but rather on the stochastic

redistribution of CENP-A (Figure 4.5A). Finally, we compared CENP-A

signals directly to a calibrated fluorescent standard (Figure 4.5E). Despite

the independent nature of these strategies, they all come to a very similar

conclusion. Thus, we demonstrate that typical centromeres in human RPE

cells contain ~400 molecules of CENP-A. While there is some debate on the

composition of CENP-A nucleosomes (Black & Cleveland 2011; Henikoff &

Furuyama 2012), current evidence strongly favors a canonical arrangement

harboring two copies of CENP-A (Bassett et al., 2012; Hasson et al., 2013;

Padeganeh et al., 2013; Sekulic et al., 2010; Tachiwana et al., 2011). Hence,

our numbers, correspond to 200 CENP-A nucleosomes in interphase, which

are split into 100 nucleosomes on mitotic chromosomes (Figure 4.8B).

Epigenetic centromere inheritance is achieved by quantitative re-

distribution of CENP-A across cell division cycles (Bodor et al., 2013; Jansen

et al., 2007). We find that rather than ensuring that each daughter receives

exactly half, redistribution of CENP-A is random (Figure 4.5B, C). Because

this regulation has the potential for individual centromeres to stochastically

inherit critical levels of CENP-A, the steady state must be sufficiently high to

avoid chromosome loss. Although the critical amount of CENP-A is not


185

known, HeLa cell viability is lost if CENP-A levels are reduced to 33% (Black

et al., 2007), i.e. 44 nucleosomes (see Figure 4.7H). Conversely, we show

here that CAG/- cells are viable at 40% of RPE levels (80 nucleosomes).

Consequently, we estimate that the critical number of nucleosomes that

must be inherited, which is half of the steady state level and replenished

during G1 phase, lies between 22 and 40.Using these values, we calculated

the chance that a cell inherits critically low levels of CENP-A on any of its

centromeres (Figure 4.8C). We demonstrate that at a steady state of 200

nucleosomes per centromere, less than one in 1016 cell divisions will give rise

to a centromere containing 40 CENP-A nucleosomes or less (Figure 4.8C,

left). Thus, the odds of inheriting a critical amount of CENP-A at wildtype

steady state levels is negligible. Conversely, with 100 nucleosomes at steady

state, the chance of a chromosome inheriting even the most stringent critical

level of 22 nucleosomes is close to 10-6 (Figure 4.8C, right), which may pose

a significant problem e.g. during development of an organism. Conversely,

although critical levels would be reached even less frequently if centromeres

contained a steady state of e.g. 300 CENP-A nucleosomes, this degree of

accuracy may be superfluous and not outweigh the cost of maintaining a

large centromere size. Therefore, we argue that the number of CENP-A

molecules found on human centromeres is optimized for robust epigenetic

inheritance and centromeric function.

Previously, it has been shown that CENP-A is interspersed with both

H3.1 and H3.3 at the centromere (Blower et al., 2002; Dunleavy et al., 2011;

Ribeiro et al., 2010; Sullivan and Karpen, 2004; Sullivan et al., 2011).

Indeed, based on the average size of the centromeric chromatin domain we

estimate that 200 CENP-A nucleosomes represent only ~4% of all

centromeric nucleosomes (see Figure 4.8A for calculation). Surprisingly, we

find that the majority of chromatin bound CENP-A is located outside the

centromere. Indeed, a recent study found that a proportion of CENP-A

containing nucleosomes also exist in non-centromeric chromatin of HeLa

cells, and is assembled by DAXX, a major chaperone of histone H3.3

Chapter 4

186

Figure 4.8 A quantitative view of human centromeric chromatin. (A) Estimated ratio and distribution of CENP-A (red)

and H3 (grey) at the centromere and on non-centromeric loci (genome) in interphase cells. Estimations assume 2

CENP-A molecules per nucleosome (Hasson et al. 2013; Bassett et al. 2012; Sekulic et al. 2010; Tachiwana et al. 2011;

Padeganeh et al. 2013); 200 bp nucleosome spacing; 2.5 x106 bp centromere domain (Lee et al. 1997; Sullivan et al.

1996), 40% of which contains CENP-A (Sullivan et al. 2011); 6 x109 bp diploid genome, 200 CENP-A nucleosomes per

centromere; 2.5 x104 CENP-A nucleosomes outside of centromeres [9.1 x104 molecules per cell (Figure 4.2F), of which

74% is in chromatin (Figure 4.4B) and 0.44% at each centromere (Figure 4.2B)]. The centromeric, non-centromeric

chromatin, and unincorporated fractions of CENP-A are indicated in green, blue, and black, respectively. (B) On average,

~100 CENP-A nucleosomes are present per mitotic centromere due to redistribution onto replicated sister chromatids

(Bodor et al. 2013; Jansen et al. 2007), although the exact number depends on the available total pool. Excess CENP-A

could either lead to an increased CENP-A domain or to a higher density of CENP-A within a domain of fixed size. This

pool forms an excess to recruit downstream centromere and kinetochore complexes and ultimately provides microtubule

binding sites for ~17 kinetochore microtubules (McEwen et al. 2001). To avoid mitotic errors, a critical amount of

CENP-A is required (dashed lines). (C) Graph representing the chance of at least one centromere in a cell (with 46

chromosomes) reaching critically low levels of CENP-A by random segregation of pre-existing CENP-A nucleosomes.

Calculations were performed for varying levels of critical nucleosome numbers at a fixed steady state of 200 (left), or by

varying the steady state number at a fixed critical level of 22 (right). Red bars are identical calculations.


187

(Lacoste et al., 2014). In addition, detectable levels of non-centromeric

CENP-A have been observed in budding yeast (Camahort et al., 2009) and

chicken DT40 cells (Shang et al., 2013). Here, we quantify this pool in

human RPE cells and while there is more than twice as many non-

centromeric CENP-A nucleosomes than there are centromeric ones, this

only represents <0.1% of all nucleosomes in the genome and thus CENP-A is

~50-fold enriched (per unit length of DNA) at centromeres (Figure 4.8A).

This result may explain how, despite being outnumbered 25:1 by other H3

variants at the centromere, CENP-A can still accurately specify the

centromeric locus. This hypothesis may be tested by creating artificial

CENP-A binding sites (e.g. using the LacO/LacI system) of different known

sizes and determining the threshold at which centromeres can be formed.

Interestingly, the study by Lacoste and co-workers showed that the

extra-centromeric CENP-A is not randomly distributed, but enriched at sites

of high histone turnover (Lacoste et al., 2014). Our finding that CENP-T,

CENP-C, and Hec1 do not quantitatively correlate with CENP-A levels

(Figure 4.6A) argues that not each (non-centromeric) CENP-A nucleosome

is able to recruit downstream centromere components. It would be

interesting to determine to what extent other centromere and kinetochore

proteins are present throughout the genome and whether they are also

enriched at extra-centromeric CENP-A hotspots. This question is

particularly relevant since it has been observed that downstream centromere

components may affect centromeric CENP-A levels (Carroll et al., 2009,

2010; Hori et al., 2013; Okada et al., 2006). A critical combination of

components at such ‘hotspots’ may trigger neocentreomere formation, the

mechanisms of which are still unresolved.

Previously, it has been observed that at very high levels of

overexpression, CENP-A ceases to be centromere restricted (Gascoigne et

al., 2011; Heun et al., 2006; Van Hooser et al., 2001). Instead, here we show

that within a 6-fold range of expression levels, the CENP-A loading

machinery has a constant efficiency, which maintains a strict ratio between

Chapter 4

188

the centromeric and total pools of CENP-A. Thus, within a physiological

range, centromeric CENP-A levels are regulated by a mass action-like

mechanism, where the loading efficiency is independent of the expression

levels. This mechanism ensures that with fluctuating expression levels,

CENP-A remains mainly centromere restricted, and may prevent potential

neocentromere seeding.

Remarkably, varying the amount of CENP-A at centromeres during

perpetual growth in culture does not affect the levels of several other

centromeric proteins. One possible explanation for this is that there is a

fixed subset of ‘active’ CENP-A nucleosomes that is responsible for

recruiting downstream components, even if the total amount of CENP-A is

variable. Alternatively, an excess of CENP-A could form a chromatin domain

that provides a ‘platform’ for recruitment of a centromere complex of fixed

size. Surprisingly, however, we find that a critical amount of CENP-A for

prevention of micronuclei is reached even before downstream centromere

and kinetochore protein levels are affected (Figure 4.6, 4.8B).

Our analysis indicates that the distribution of CENP-A among

centromeres within one cell is generally uniform. However, in agreement

with prior publications, we find that both the Y-centromere as well as a

human neocentromere have lower CENP-A levels (Amor et al. 2004; Irvine

et al. 2004). Interestingly, both these centromere types are atypical in that

they are formed on relatively small genomic loci: ~600 kb for the Y-

centromere (Abruzzo et al., 1996) and ~300 kb for the NeoCEN-4 (Hasson

et al., 2013), whereas autosomes and the X-chromosome have alpha-

sattellite arrays of several magabases in size (Lo et al., 1999; Mahtani and

Willard, 1990; Wevrick and Willard, 1989). In addition, in contrast to

canonical centromeres, neither the Y-centromere nor neocentromeres

recruit the sequence specific DNA binding protein CENP-B (Amor et al.,

2004; Earnshaw et al., 1987), which has been hypothesized to alter the 3D

structure of centromeric chromatin (Pluta et al., 1992). The presence of

CENP-B binding sites has recently been shown to have a role in phasing


189

CENP-A nucleosomes (Hasson et al., 2013), and to cooperate with CENP-A

in kinetochore function (Fachinetti et al., 2013), and may therefore be

involved in regulation of centromeric CENP-A levels as well. Furthermore,

high resolution analysis of a human neocentromere reveals a non-random

distribution of CENP-A (Hasson et al. 2013), where individual nucleosome

positions are occupied in anywhere between 0.5% to 80% of cells (Figure

4.7K, L). Thus, despite specific DNA sequences being neither sufficient nor

required for centromere identity (Amor et al., 2004; Earnshaw and Migeon,

1985; Marshall et al., 2008; Voullaire et al., 1993), the amount of CENP-A at

centromeres likely results from a combination of a systematic cellular

mechanism with a contribution of local sequence or chromatin features.

In conclusion, several key mechanistic insights follow from our findings.

First, while CENP-A nucleosomes are highly enriched at the centromere,

most CENP-A is distributed at low levels throughout chromatin. This

indicates that there is no exclusive pathway that restricts CENP-A assembly

to centromeres. Nevertheless, we propose that the ample number of CENP-A

nucleosomes facilitates a robust epigenetic signal that can absorb

fluctuations in CENP-A inheritance and assembly in order to faithfully

maintain centromere identity. Secondly, the requirement for a sizable

number of CENP-A nucleosomes to perpetuate an active centromere reduces

the likelihood for inadvertent detrimental neocentromere seeding without

the need for a tightly restricted assembly mechanism. In addition, the fixed

ratio between total and centromeric CENP-A levels may prevent excess

CENP-A from accumulating at high density at non-centromeric loci, thus

further reducing the probability of neocentromere formation. Finally, the

number of centromeric CENP-A nucleosomes represents an ample pool of

which only a subset is required to nucleate otherwise self-organized

centromere and kinetochore complexes. In summary, from our analysis an

integrated view of centromeric architecture, size, and regulation emerges

(Figure 4.8) that provides a basis to explain the self-propagating nature of

the epigenetic centromere.

Chapter 4

190

MATERIAL & METHODS

Cell culture and construction.

All human cell lines used were grown at 37°C, 5% CO2. Cells were grown

in DMEM/F-12 (RPE), DMEM (HeLa, U2OS, PDNC-4), MEM (primary

fibroblasts; Coriell GM06170), McCoy’s 5A (HCT-116), or RPMI-1640

(DLD-1) cell culture media. Media were supplemented with 10% fetal bovine

serum (FBS), 2 mM glutamine, 1 mM sodium pyruvate (SP), 100 U/ml

penicillin and 100 μg/ml streptomycin, with the following exceptions: for

RPE cells SP was substituted for 14.5mM sodium bicarbonate; for HeLa

newborn calf serum was used instead of FBS; for fibroblasts 15% FBS was

used; for DLD-1 cells SP was omitted; and both SP and glutamine were

omitted for HCT-116 cells. During live cell imaging, culture medium was

replaced with Leibowitz’s L-15 medium containing 10% FBS and 2 mM

glutamine. LacI-GFP::LacO HCT-116 cells [gift from Duane Compton

(Thompson & Compton 2011)] were selected alternatingly with 2 μg/ml

blasticidin and 300 μg/ml hygromycin; PDNC-4 cells were selected with 100

μg/ml neomycin. All media and supplements were purchased from Gibco.

All targeted cell lines are derived from wildtype hTERT RPE (CA+/+).

Gene targeting was achieved by adeno-associated virus (AAV) mediated

delivery of targeting constructs essentially as described (Berdougo et al.

2009), except in the case if CAG/-cells (see below). The CA+/F cell line was

created by inserting loxP sites surrounding CENP-A exons 2 and 4 as

described previously (Fachinetti et al. 2013). The CA+/- cell line was created

by targeting CA+/F cells with a construct lacking 1373 bp of the CENP-A gene

(from 43 bp upstream of exon 2 to 134 bp downstream of exon 4) including

the essential CENP-A targeting domain (Black et al. 2007). CAY/- cells were

created by sequential targeting of a first CENP-A allele with the targeting

construct inserting loxP sites flanking exon 3 and 4 as described above and

the second allele by targeting EYFP (carrying citrine and monomerization

mutations: Q69M, A206K) in frame with the CENP-A gene, immediately


191

prior to the stop codon in exon 4. The floxed allele was subsequently

removed by retroviral delivery of HR-MMPCreGFP, a “Hit and Run” Cre

vector, as described (Silver & Livingston 2001). CAG/- cells were created from

an independent CA+/- clone where the remaining intact CENP-A allele was

targeted with EGFP using a FACS-based strategy that we developed

previously (Mata et al. 2012). Targeting resulted in insertion of the EGFP

ORF directly downstream the last coding sequence in exon 4, just upstream

of the endogenous stop codon, without insertion of any selectable marker

gene. CAY/-+OE cells were created by stable transfection of and selection (5

μg/ml blasticidin) for a CENP-A-YFP expression vector (pBOS-Blast)

bearing a CENP-A-YFP fusion protein identical to that of the endogenous

knockin locus) in CAY/- cells. CAY/-+H2B-RFP and CA+/++H2B-RFP cell lines

were created by stable transfection of and selection (5 μg/ml puromycin) for

a H2B-RFP expression vector (Black et al. 2007) in CAY/- and CA+/+ cells,

respectively. All cell lines were monoclonally sorted by FACS.

For the transient transfection experiment (Figure 4.1F), wildtype HeLa

cells were first synchronized in S phase by addition of 2 mM thymidine.

After 17 hours, cells were released using 24 μM deoxycytidine and

simultaneously transfected with untagged, wildtype CENP-A and/or HJURP

expression vectors (or an empty vector) in combination with an EYFP-

CENP-C expression vector (Shah et al. 2004) (2:2:1 proportion). 9 hours

later, thymidine was re-added for an additional 15 hours, at which point cells

were again released with deoxycytidine for 9 hours. A final thymidine arrest

was performed and after 15 hours cells were fixed. Only cells expressing the

positive transfection marker EYFP-CENP-C were analyzed. All stable and

transient transfections were performed using Lipofectamine LTX

(Invitrogen) according to the manufacturer’s instructions.

Immunoblotting and cell fractionation.

Samples were prepared in Laemmli buffer, separated by SDS-PAGE, and

transferred onto nitrocellulose membranes. Whole cell extracts (WCE) were

Chapter 4

192

prepared by lysing cells directly in sample buffer, to ensure that the entire

cellular protein pool remained present in the sample. Recombinant

CENP-A/H4-complexes were purified as described previously (Black et al.,

2004) and mixed with WCE from chicken DT40 cells to bring the overall

concentration of the purified protein preps to a level comparable to that of

RPE WCE. Absence of cross-recognition of human CENP-A antibody to

chicken protein was confirmed by omission of recombinant human CENP-A

protein in DT40 extracts (Figure 4.2D, second lane). Alternatively,

recombinant CENP-A/H4 was spiked into RPE cell extracts. Results

obtained from the two methods are comparable [95.3 ± 14.0 ng (n=8) and

75.4 ± 5.4 ng (n=2), respectively; p>0.5]. Cellular CENP-A quantity was

determined by comparison of fluorescence derived from cellular and

purified CENP-A. The following antibodies and dilutions were used:

CENP-A [Cell Signaling Technology, #2186 or (Ando et al., 2002)] at 1:1000

or tissue culture supernatant at 1:400, respectively; α-tubulin (DM1A, Sigma

Aldrich) at 1:5000; HJURP [gift from Dan Foltz, (Foltz et al. 2009)] at

1:10000; Mis18BP1 (A302-825A, Bethyl Laboratories, Inc.) at 1:2000;

H4K20me2 (ab9052, Abcam) at 1:1000. IRDye800CW-coupled anti-mouse

or anti-rabbit (Licor Biosciences) and DyLight680-coupled anti-mouse or

anti-rabbit (Rockland Immunochemicals) secondary antibodies were used

prior to detection on an Odyssey near-infrared scanner (Licor Biosciences).

Immunoblot signals were quantified using the Odyssey software (Licor

Biosciences), and a linear response was confirmed over a 32-fold range

(Figure 4.2E). Target protein signals were normalized to the α-tubulin

loading control signal to correct for slight deviations in cell concentration

between extracts of different RPE cell lines.

Cell fractionation was performed for CAY/-+H2B-RFP cells after cell lysis

in ice cold buffer consisting of 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 0.5

mM EDTA, 1% Triton X-100, 1 mM DTT, and a mix of protease inhibitors [1

mM PMSF, 1 μg/ml leupeptin, 1 μg/ml pepstatin, and aprotinin (Sigma

A6279, 1:1000 dilution)]. Soluble proteins were separated from the


193

insoluble fraction by centrifugation at 21000 g at 4°C and resuspended in an

equal volume of lysis buffer. Both supernatant and pellet fractions were

incubated with 1.25 U/μl of benzonase nuclease (Novagen) on ice for 30

minutes prior to denaturation in Laemmli sample buffer.

Microscopy.

Imaging was performed on an Andor Revolution XD system, controlling

an inverted microscope (Nikon Eclipse-Ti), an iXonEM+ EMCCD camera

(DU-897, Andor), a CSU-X1 spinning disk unit (Yokogawa), a laser

combiner/multi-port switch system (Andor) and a motorized stage (Prior),

controlled by MicroManager software (Edelstein et al. 2010). Images were

collected using a Nikon 100X, 1.4NA, Plan Apo oil immersion objective

(fixed cell imaging) or a Nikon 60X, 1.2 NA, Plan Apo VC water immersion

objective (live cell imaging) at 1x binning. For live cell imaging, the

temperature of the chamber was maintained at 37°C.

Fluorescence lifetime measurements.

Cells grown on glass coverslips were fixed and mounted as described

(Bodor et al. 2012) and imaged using a Zeiss LSM710 coupled to a motorized

stage of an upright Zeiss Axio Examiner microscope equipped with a 63x

Plan-Apo NA 1.4 oil immersion objective. A Coherent Chameleon Vision II

multi-photon Ti-Sapphire laser was used to excite EYFP samples. All images

were 512 x 512 pixels in size, with a pixel size of 0.09 μm. For all samples, an

optimal setting of the laser power and PMT voltage was chosen to avoid

pixel saturation and minimize photobleaching. The CLSM settings were kept

constant so that valid comparisons could be made between measurements

from different samples. Fluorescence lifetime imaging microscopy (FLIM)

was performed by measuring the decay rate of EYFP using a Becker & Hickl

time-correlated single photon counting hybrid detector coupled to the

confocal LSM710 setup. The SPCImage (Becker & Hickl) software was

utilized to perform single exponential fitting for each pixel location.

Chapter 4

194

Immunofluorescence and mitotic spreads.

Cell fixation, immunofluorescence and DAPI staining was performed as

described previously (Bodor et al. 2012). The following antibodies and

dilutions were used: CENP-A [gift from Tatsuo Fukagawa (Ando et al.

2002)] tissue culture supernatant at 1:100, rabbit polyclonal CENP-B

(sc22788, Santa Cruz Biotechnology) at 1:100, tissue culture supernatant

from mouse hybridomas expressing monoclonal CENP-B (Earnshaw et al.

1987) at 1:4, CENP-C (Foltz et al. 2009) at 1:10000, CENP-T [gift from Dan

Foltz (Barnhart et al. 2011)] at 1:1000, Hec1 (9G3.23; MA1-23308, Pierce) at

1:100, ACA (anti-centromere antibodies; 83JD, gift from Kevin Sullivan) at

1:100. Fluorescent secondary antibodies were obtained from Jackson

ImmunoResearch or Rockland ImmunoChemicals and used at a dilution of

1:200. Immunofluorescence signals of Figure 4.1C, 4.5E, 4.6B, 4.7G were

automatically quantified using the CRaQ method as described previously

(Bodor et al. 2012) using CENP-T or CENP-C as a centromere reference.

Hec1 levels were measured exclusively in prometaphase or metaphase

(based on DAPI staining) of unperturbed cells. Micronuclei were scored

based on DAPI staining.

Mitotic spreads were performed after mitotic shake-off of cells arrested

overnight (~16 hours) in 250 ng/ml nocodazole. 25000 cells/ml were

swollen in 75mM KCl and 5000 cells were cytospun onto coverslips using a

Cytopro 7620 cytocentrifuge (Wescor Inc.) for 4 minutes, at 1200 rpm, high

acceleration. Cells were then fixed and processed for immunofluorescence as

described above. Average centromere signals of both sisters were measured

after background correction, by subtracting the minimum pixel value from

the maximum of a box of 5x5 pixels around each sister centromere. Specific

chromosomal markers were used as described in the text to detected

centromeres of interest and signals were normalized to the average of all

centromeres of the same cell spread.


195

Quantification of the centromeric CENP-A copy number.

CA+/+ cells were mixed with CAY/-, CAG/-, or CAY/-+OE cells at a ~1:4 ratio

on 35mm glass-bottom petri dishes (MatTek Corporation). Non-cell

permeable dextran-AlexaFluor647 (10000 MW, Molecular Probes) was

added at 2–4 μg/ml to stain the medium outside of cells (Figure 4.2A, I). To

minimize oversampling, individual live cells were imaged at 500 nm axial

resolution (close to the resolution limit of the objective) spanning the entire

cell volume. Images were flatfield corrected for unequal illumination using

the signal of a uniform fluorescent slide and the “Shading Corrector” plugin

for FIJI. For each axial section, the cell outline was determined based on

absence of dextran-AlexaFluor647 staining and the integrated fluorescence

intensities inside the cell outline as well as those of 1–3 independent

background regions per section were determined. Background corrected

signals from all sections were summed to determine the total cellular

fluorescence. Fluorescence measurements of CAY/-, CAG/-, or CAY/-+OE cells

were corrected for autofluorescence by subtraction of average per pixel

fluorescence intensity of non-fluorescent CA+/+ cells from the same dish.

Alternatively, CA+/++H2B-RFP and CAY/-+H2B-RFP cells were mixed and no

dextran was added to the medium. In this case, the H2B-RFP signal was

used to determine the nuclear volume and total nuclear fluorescence was

determined as described above for the total cellular volume. Automated

centromere detection was performed by an analogous algorithm to a

previous study (Bodor et al. 2012; Bodor et al. 2013), where diffraction

limited spots are detected based on their size, circularity, and feret’s

diameter. Centromere signals were measured by integrating the intensity of

a 5 pixel diameter surrounding each centromere in the appropriate axial

section. Local background fluorescence was derived by measuring the

difference in intensity between concentric circles of 5 and 7 pixel diameter,

and subtracted from centromeric signals (Hoffman et al. 2001). In addition,

centromeric signals were corrected for axial oversampling. For this,

diffraction limited spots of yellow/green PS-Speck fluorescent beads

Chapter 4

196

(Molecular Probes) were measured in multiple plains. The sum intensity of

individual beads from all these plains was compared to the signal in the

plain with the maximum signal (i.e. the focal plane). The percentage of

centromeric fluorescence was determined in relationship to the total

fluorescence of each individual cell.

To allow for cell cycle staging of CAY/- cells, transduction with

hCdt1(30/120)-RFP was performed using the BacMam2.0 baculovirus

system (Invitrogen). Expression levels of transduced protein were allowed to

stabilize for 3 days prior to analysis. Individual cells were followed by live

cell microscopy using DIC and RFP signals. Nuclear RFP signals were

tracked every ~2 hours to monitor their cell cycle progression. Imaging of

YFP (CENP-A) and Cy5 (cellular volume) was performed as described above.

Analysis of the centromeric CENP-A ratio was performed as described

above, but restricted to cells in which RFP levels were decreasing at the

specific timepoint of analysis (to exclude cells in G1 phase) and which did

not enter mitosis or showed an increase in RFP levels for at least the

following 3–4 hours (to exclude cells in G2 phase). Centromeric ratio was

compared to non-transduced, randomly cycling cells (Figure 4.3C) or

randomly cycling cells that were transduced, but not followed over time

(Figure 4.3—S1). For these experiments, wildtype cells used to measure

cellular autofluorescence were seeded on a separate dish.

Stochastic fluctuation measurements.

CAY/-, CAG/- or CAY/-+OE cells were treated with nocodazole (250–500

ng/μl) for 9 hours, after which cells were fixed and processed for

immunofluorescence as described above. Sister centromere pairs were

identified by CENP-B staining and GFP or YFP fluorescence intensity of

each sister was measured and background corrected by subtracting the

minimum pixel value of a 5 pixel diameter circle from the maximum value.

The difference (δ) in fluorescence intensity as well as the sum (Σ) intensity

of the two sisters was determined. The fluorescence intensity per segregating


197

unit (α) was determined from the average δ2/Σ of all centromere pairs of the

same experiment and cell line. The number of segregating units on each

centromere was calculated as Σ/α, as described previously (Rosenfeld et al.,

2005, 2006) and in Figure 4.5A. In addition to sister centromeres, three

independent rounds of random centromere pairing between all centromeres

measured in a single experiment on CAG/- cells were performed and

centromeric CENP-A-GFP units based on these pairings were quantified in

Figure 4.5—S1E.

Yeast growth and imaging.

4kb-LacO, LacI-GFP S. cerevisiae [gift from Kerry Bloom (Lawrimore et

al. 2011)] were grown in minimal synthetic media [Yeast nitrogen base

(Sigma) + complete synthetic defined single drop-out medium lacking uracil

and histidine (MP Biomedicals)], supplemented with 2% D (+)Glucose

(Merck). Prior to imaging, log phase cells (OD600 of ~0.7) were transferred

onto a 2% low melting agarose pad and sealed under a coverslip with VALAP

(1:1:1 vaseline:lanolin:paraffin). CAG/- cells were grown on 35mm glass-

bottom petri dishes and yeast and human cells were imaged using identical

settings during the same microscopy session. Fluorescence intensity of

centromeres and Lac-arrays were quantified after background correction

(maximum minus minimum of a 5x5 pixel box).

Integrating ChIP-seq and quantitative data of CENP-A at a human

neocentromere.

CENP-A ChIP-Seq data from the PDNC-4 neocentromere cell line

(Accession #GSE44724) was processed as previously described (Hasson et

al. 2013). Briefly, paired-end ChIP-Seq reads were aligned to the human

genome build hg19 with Bowtie2 version 2.0.0 using paired-end mode.

Reads were aligned by using a seed length of 50 bp, and only the single best

alignment per read with up to two mismatches was reported in the SAM file.

The aligned mate pairs were joined in MATLAB by requiring ≥95% overlap

Chapter 4

198

identity. The joined reads were aligned to the PDNC-4 neocentromere and

only reads which mapped with 100% identity were used in the subsequent

analysis. Nucleosome positions at the neocentromere were determined using

the ‘findpeaks’ function in MATLAB. The probability of CENP-A occupancy

at a given position was determined according to the following formula: (total

reads overlying that position) X (216 CENP-A nucleosomes [Figure 4.7J]) /

(total reads mapping to the entire neocentromere).

Calculation of the chance of reaching critical CENP-A levels after

random segregation.

All calculations represented in Figure 4.8C were performed in R. For

these calculations we assume that CENP-A is inherited following a

binominal distribution, consistent with our findings (Figure 4.5, 4.5—S1A,

C). To determine the chance (X) of any chromosome reaching critical levels

of CENP-A, the ‘pbinom’ function was used to calculate the fraction of a

binomial distribution [where p = 0.5 and n (steady state number of

nucleosomes) = 200 or was varied as indicated] that is either below a critical

value (c = 22, or varied as indicated) or above acritical value (n−c). To

determine the chance that any chromosome in a cell (containing 46

chromosomes) reaches critical levels, we calculated the chance that 46

independent centromeres do not reach critical levels and subtracted this

chance from 1, i.e.: [1− (1−X)46].


199

REFERENCES

Abruzzo MA, Griffin DK, Millie EA, Sheean LA & Hassold TJ (1996) The effect of Y-chromosome alpha-satellite array length on the rate of sex chromosome disomy in human sperm. Hum. Genet. 97: 819–823

Allshire RC & Karpen GH (2008) Epigenetic regulation of centromeric chromatin: old dogs, new tricks? Nat. Rev. Genet. 9: 923–937


Ando S, Yang H, Nozaki N, Okazaki T & Yoda K (2002) CENP-A, -B, and -C chromatin complex that contains the I-type alpha-satellite array constitutes the prekinetochore in HeLa cells. Mol. Cell. Biol. 22: 2229–2241



Berdougo E, Terret M-E & Jallepalli PV (2009) Functional dissection of mitotic regulators through gene targeting in human somatic cells. Methods Mol. Biol. Clifton NJ 545: 21–37

Black BE & Cleveland DW (2011) Epigenetic Centromere Propagation and the Nature of CENP-A Nucleosomes. Cell 144: 471–479


Black BE, Jansen LET, Maddox PS, Foltz DR, Desai AB, Shah JV & Cleveland DW (2007) Centromere identity maintained by nucleosomes assembled with histone H3 containing the CENP-A targeting domain. Mol. Cell 25: 309–322

Blower MD, Sullivan BA & Karpen GH (2002) Conserved organization of centromeric chromatin in flies and humans. Dev. Cell 2: 319–330


Bodor DL, Valente LP, Mata JF, Black BE & Jansen LET (2013) Assembly in G1 phase and long-term stability are unique intrinsic features of CENP-A nucleosomes. Mol. Biol. Cell 24: 923–932


Chapter 4

200



Cheeseman IM, Chappie JS, Wilson-Kubalek EM & Desai A (2006) The conserved KMN network constitutes the core microtubule-binding site of the kinetochore. Cell 127: 983–997


Coffman VC, Wu P, Parthun MR & Wu J-Q (2011) CENP-A exceeds microtubule attachment sites in centromere clusters of both budding and fission yeast. J. Cell Biol. 195: 563–572

DeLuca JG, Gall WE, Ciferri C, Cimini D, Musacchio A & Salmon ED (2006) Kinetochore microtubule dynamics and attachment stability are regulated by Hec1. Cell 127: 969–982



Earnshaw WC & Migeon BR (1985) Three related centromere proteins are absent from the inactive centromere of a stable isodicentric chromosome. Chromosoma 92: 290–296

Earnshaw WC, Sullivan KF, Machlin PS, Cooke CA, Kaiser DA, Pollard TD, Rothfield NF & Cleveland DW (1987) Molecular cloning of cDNA for CENP-B, the major human centromere autoantigen. J. Cell Biol. 104: 817–829

Edelstein A, Amodaj N, Hoover K, Vale R & Stuurman N (2010) Computer control of microscopes using µManager. Curr. Protoc. Mol. Biol. Chapter 14: Unit14.20




Ford JH, Schultz CJ & Correll AT (1988) Chromosome elimination in micronuclei: a common cause of hypoploidy. Am. J. Hum. Genet. 43: 733–740


201


Furuyama S & Biggins S (2007) Centromere identity is specified by a single centromeric nucleosome in budding yeast. Proc. Natl. Acad. Sci. U. S. A. 104: 14706–14711



Haase J, Mishra PK, Stephens A, Haggerty R, Quammen C, Taylor RM 2nd, Yeh E, Basrai MA & Bloom K (2013) A 3D map of the yeast kinetochore reveals the presence of core and accessory centromere-specific histone. Curr. Biol. CB 23: 1939–1944


Henikoff S, Ahmad K, Platero JS & Steensel B van (2000) Heterochromatic deposition of centromeric histone H3-like proteins. Proc. Natl. Acad. Sci. 97: 716–721

Henikoff S & Furuyama T (2012) The unconventional structure of centromeric nucleosomes. Chromosoma 121: 341–352

Heun P, Erhardt S, Blower MD, Weiss S, Skora AD & Karpen GH (2006) Mislocalization of the Drosophila centromere-specific histone CID promotes formation of functional ectopic kinetochores. Dev. Cell 10: 303–315

Hoffelder DR, Luo L, Burke NA, Watkins SC, Gollin SM & Saunders WS (2004) Resolution of anaphase bridges in cancer cells. Chromosoma 112: 389–397

Hoffman DB, Pearson CG, Yen TJ, Howell BJ & Salmon ED (2001) Microtubule-dependent changes in assembly of microtubule motor proteins and mitotic spindle checkpoint proteins at PtK1 kinetochores. Mol. Biol. Cell 12: 1995–2009

Van Hooser AA, Ouspenski II, Gregson HC, Starr DA, Yen TJ, Goldberg ML, Yokomori K, Earnshaw WC, Sullivan KF & Brinkley BR (2001) Specification of kinetochore-forming chromatin by the histone H3 variant CENP-A. J. Cell Sci. 114: 3529–3542


Irvine DV, Amor DJ, Perry J, Sirvent N, Pedeutour F, Choo KHA & Saffery R (2004) Chromosome size and origin as determinants of the level of CENP-A incorporation into human centromeres. Chromosome Res. Int. J. Mol. Supramol. Evol. Asp. Chromosome Biol. 12: 805–815


Chapter 4

202

Joglekar AP, Bouck DC, Molk JN, Bloom KS & Salmon ED (2006) Molecular architecture of a kinetochore-microtubule attachment site. Nat. Cell Biol. 8: 581–585

Joglekar AP, Bouck D, Finley K, Liu X, Wan Y, Berman J, He X, Salmon ED & Bloom KS (2008) Molecular architecture of the kinetochore-microtubule attachment site is conserved between point and regional centromeres. J. Cell Biol. 181: 587–594

Johnston K, Joglekar A, Hori T, Suzuki A, Fukagawa T & Salmon ED (2010) Vertebrate kinetochore protein architecture: protein copy number. J. Cell Biol. 189: 937–943

Karachentsev D, Druzhinina M & Steward R (2007) Free and chromatin-associated mono-, di-, and trimethylation of histone H4-lysine 20 during development and cell cycle progression. Dev. Biol. 304: 46–52


Lawrimore J, Bloom KS & Salmon ED (2011) Point centromeres contain more than a single centromere-specific Cse4 (CENP-A) nucleosome. J. Cell Biol. 195: 573–582

Lee C, Wevrick R, Fisher RB, Ferguson-Smith MA & Lin CC (1997) Human centromeric DNAs. Hum. Genet. 100: 291–304


Lo AW, Liao GC, Rocchi M & Choo KH (1999) Extreme reduction of chromosome-specific alpha-satellite array is unusually common in human chromosome 21. Genome Res. 9: 895–908


Mahtani MM & Willard HF (1990) Pulsed-field gel analysis of alpha-satellite DNA at the human X chromosome centromere: high-frequency polymorphisms and array size estimate. Genomics 7: 607–613


Mata JF, Lopes T, Gardner R & Jansen LET (2012) A rapid FACS-based strategy to isolate human gene knockin and knockout clones. PloS One 7: e32646

McEwen BF, Chan GKT, Zubrowski B, Savoian MS, Sauer MT & Yen TJ (2001) CENP-E Is Essential for Reliable Bioriented Spindle Attachment, but Chromosome Alignment Can Be Achieved via Redundant Mechanisms in Mammalian Cells. Mol. Biol. Cell 12: 2776–2789


203

Meluh PB, Yang P, Glowczewski L, Koshland D & Smith MM (1998) Cse4p is a component of the core centromere of Saccharomyces cerevisiae. Cell 94: 607–613



Padeganeh A, Ryan J, Boisvert J, Ladouceur A-M, Dorn JF & Maddox PS (2013) Octameric CENP-A nucleosomes are present at human centromeres throughout the cell cycle. Curr. Biol. CB 23: 764–769


Palmer DK, O’Day K, Wener MH, Andrews BS & Margolis RL (1987) A 17-kD centromere protein (CENP-A) copurifies with nucleosome core particles and with histones. J. Cell Biol. 104: 805–815

Pluta AF, Saitoh N, Goldberg I & Earnshaw WC (1992) Identification of a subdomain of CENP-B that is necessary and sufficient for localization to the human centromere. J. Cell Biol. 116: 1081–1093


Régnier V, Vagnarelli P, Fukagawa T, Zerjal T, Burns E, Trouche D, Earnshaw W & Brown W (2005) CENP-A is required for accurate chromosome segregation and sustained kinetochore association of BubR1. Mol. Cell. Biol. 25: 3967–3981

Ribeiro SA, Vagnarelli P, Dong Y, Hori T, McEwen BF, Fukagawa T, Flors C & Earnshaw WC (2010) A super-resolution map of the vertebrate kinetochore. Proc. Natl. Acad. Sci. U. S. A. 107: 10484–10489

Rosenfeld N, Perkins TJ, Alon U, Elowitz MB & Swain PS (2006) A fluctuation method to quantify in vivo fluorescence data. Biophys. J. 91: 759–766

Rosenfeld N, Young JW, Alon U, Swain PS & Elowitz MB (2005) Gene regulation at the single-cell level. Science 307: 1962–1965

Sakaue-Sawano A, Kurokawa H, Morimura T, Hanyu A, Hama H, Osawa H, Kashiwagi S, Fukami K, et al (2008) Visualizing Spatiotemporal Dynamics of Multicellular Cell-Cycle Progression. Cell 132: 487–498

Du Sart D, Cancilla MR, Earle E, Mao JI, Saffery R, Tainton KM, Kalitsis P, Martyn J, Barry AE & Choo KH (1997) A functional neo-centromere formed through activation of a latent human centromere and consisting of non-alpha-satellite DNA. Nat. Genet. 16: 144–153

Schittenhelm RB, Althoff F, Heidmann S & Lehner CF (2010) Detrimental incorporation of excess Cenp-A/Cid and Cenp-C into Drosophila centromeres is

Chapter 4

204

prevented by limiting amounts of the bridging factor Cal1. J. Cell Sci. 123: 3768–3779



Shah JV, Botvinick E, Bonday Z, Furnari F, Berns M & Cleveland DW (2004) Dynamics of centromere and kinetochore proteins; implications for checkpoint signaling and silencing. Curr. Biol. CB 14: 942–952

Shang W-H, Hori T, Martins NMC, Toyoda A, Misu S, Monma N, Hiratani I, Maeshima K, Ikeo K, Fujiyama A, Kimura H, Earnshaw WC & Fukagawa T (2013) Chromosome engineering allows the efficient isolation of vertebrate neocentromeres. Dev. Cell 24: 635–648

Shelby RD, Monier K & Sullivan KF (2000) Chromatin assembly at kinetochores is uncoupled from DNA replication. J. Cell Biol. 151: 1113–1118


Silver DP & Livingston DM (2001) Self-excising retroviral vectors encoding the Cre recombinase overcome Cre-mediated cellular toxicity. Mol. Cell 8: 233–243

Stoler S, Keith KC, Curnick KE & Fitzgerald-Hayes M (1995) A mutation in CSE4, an essential gene encoding a novel chromatin-associated protein in yeast, causes chromosome nondisjunction and cell cycle arrest at mitosis. Genes Dev. 9: 573–586

Sullivan BA & Karpen GH (2004) Centromeric chromatin exhibits a histone modification pattern that is distinct from both euchromatin and heterochromatin. Nat. Struct. Mol. Biol. 11: 1076–1083

Sullivan BA, Schwartz S & Willard HF (1996) Centromeres of human chromosomes. Environ. Mol. Mutagen. 28: 182–191

Sullivan LL, Boivin CD, Mravinac B, Song IY & Sullivan BA (2011) Genomic size of CENP-A domain is proportional to total alpha satellite array size at human centromeres and expands in cancer cells. Chromosome Res. Int. J. Mol. Supramol. Evol. Asp. Chromosome Biol. 19: 457–470


Thompson SL & Compton DA (2011) Chromosome missegregation in human cells arises through specific types of kinetochore-microtubule attachment errors. Proc. Natl. Acad. Sci. U. S. A. 108: 17974–17978

Utani K, Kohno Y, Okamoto A & Shimizu N (2010) Emergence of Micronuclei and Their Effects on the Fate of Cells under Replication Stress. PLoS ONE 5: e10089


205


Wevrick R & Willard HF (1989) Long-range organization of tandem arrays of alpha satellite DNA at the centromeres of human chromosomes: high-frequency array-length polymorphism and meiotic stability. Proc. Natl. Acad. Sci. U. S. A. 86: 9394–9398

Wu J-Q, McCormick CD & Pollard TD (2008) Chapter 9: Counting proteins in living cells by quantitative fluorescence microscopy with internal standards. Methods Cell Biol. 89: 253–273

Wu J-Q & Pollard TD (2005) Counting cytokinesis proteins globally and locally in fission yeast. Science 310: 310–314


Zinkowski RP, Meyne J & Brinkley BR (1991) The centromere-kinetochore complex: a repeat subunit model. J. Cell Biol. 113: 1091–1110


All experiments and analyses were performed by me, with the following

exceptions: JFM constructed and performed initial characterization of

knockout and knockin cell lines; MS and JVS performed and analyzed

experiments shown in Figure 4.2S1; AFD performed and helped analyze

experiments in Figure 4.1F; KJS and BEB performed analysis shown in

Figure 4.7K. LETJ is co-responsible for conception and design of the project.

The manuscript for this chapter was drafted and revised with help of LETJ

and constructive suggestions by all authors.

Acknowledgements

We thank Tatsuo Fukagawa (National Institute of Genetics, Shizuoka,

Japan), Dan Foltz (University of Virginia, Charlottesville, VA), Kevin

Sullivan (National University of Ireland, Galway, Ireland), David Livingston

(Dana-Farber Cancer Institute, Boston, MA), Bernardo Orr and Duane

Compton (Dartmouth Medical School, Hanover, NH), and Kerry Bloom

Chapter 4

206

(University of North Carolina, Chapel Hill, NC) for reagents, Nitzan

Rosenfeld (Cancer Research UK, Cambridge, UK) for advice, and Jorge

Carneiro (Instituto Gulbenkian de Ciência, Oeiras, Portugal) for help using

R. We thank the Confocal and Light Microscopy core facility at Dana Farber

Cancer Institute (Harvard Medical School) for providing access to the FLIM

setup. We are grateful to Alekos Athanasiadis and Monica Bettencourt-Dias

(both at Instituto Gulbenkian de Ciência, Oeiras, Portugal) for helpful

comments on the manuscript.


207

FIGURE SUPPLEMENTS

Supplement to Figure 1

Figure 4.1—S1 CENP-A expression is the rate limiting factor for centromeric CENP-A levels. (A) Pedigree of targeted

RPE cell lines used in this study. Uninterrupted lines indicate single gene-targeting events, interrupted lines indicate

multiple sequential gene-targeting events, and dashed lines indicate stable ectopic protein expression. (B, C)

Correlation of centromeric CENP-A and total cellular HJURP (B) or Mis18BP1 levels (C). Insets show quantification of

total protein levels from Figure 4.1B; n = 3–5 independent experiments. Dashed lines represent hypothetical directly

proportional relationships with indicated correlation coefficients. In the insets, the average ± SEM (n = 3–5) is shown.

Supplements to Figure 2

Figure 4.2—S1 Representative fluorescence lifetime imaging (FLIM) micrograph of a CENP-A-YFP expressing cell

(left) and quantification of indicated cellular regions (right).

Chapter 4

208

Figure 4.2—S2 Measurements of individual centromeres for CAG/- (A) and CAY/-+OE cells (B). Graphs as in Figure

4.2B. (C) Graph showing the absolute amount of centromeric CENP-A for indicated cell lines.


209

Figure 4.2—S3 Transfer efficiency of recombinant and cellular CENP-A. Immunoblots of recombinant and cellular

CENP-A from CA+/+, CAG/-, and CAY/- cells, after protein transfer onto a stack of three membranes. The fraction of

CENP-A retained on the first membrane (compared to the total signal from all three membranes) is quantified below.

While YFP- or GFP- tagged CENP-A barely passes through the membrane at all, untagged CENP-A from cell extracts or

recombinant protein preps is retained equally well on the first membrane.


Figure 4.3—S1 hCdt-1(30/120)-RFP expression allows for accurate determination of cell cycle stages and

measurements of centromeric CENP-A ratios. (A) An example trace of a cell that had entered G1 phase at the beginning

of the experiment [as determined by cellular morphology (DIC)] is shown. Graph as in in Figure 4.3B. (B) Baculoviral

transduction of hCdt-1(30/120)-RFP does not affect measurements of CENP-A-YFP. Centromeric CENP-A ratio

measurements of non-transduced cells were compared to measurements of unstaged (i.e. randomly cycling) cells

expressing hCdt-1(30/120)-RFP. Graph as in Figure 4.3C.

Chapter 4

210


Figure 4.5—S1 Stochastic fluctuations of CENP-A segregation allows for copy number measurements. (A–D) Results

as in Figure 4.5C–D for CAY/- (A–B) and CAY/-+OE cells (C–D). (E) Quantification of segregating units in CAG/- cells

based on sister centromeres (dark green) or random centromere pairs (light green; random pairs were assigned

independently three times). Asterisks indicate a significant difference from sister centromere result (t-test; p<0.0001 in

all cases). Each circle represents one centromere pair. Throughout, the average ± SEM is indicated.


211


Figure 4.6—S1 Representative images for quantifications in Figure 4.6B. Images of indicated cell lines are shown for

immunofluorescence staining of (A) CENP-C, (B) CENP-T, and (C) Hec1 (mitotic cells). Scale bars: 5 μm.

Chapter 4

212


Figure 4.7—S1 Measurements of individual centromeres for graphs in Figure 4.7. CENP-A levels are normalized to the

average of each individual cell for CEN-Lac in HCT-116 cells (A), CEN-Y in wildtype HCT-116 cells (B), CEN-Y in DLD-1

cells (C), and NeoCEN-4 in PDNC-4 cells (D). Each circle represents one centromere; circles on the same column are

individual centromeres from the same cell. Colored circle represents uniquely identified chromosome. Averages ± SEM

are indicated. Graph to the right in C as in Figure 4.7D for DLD-1 cells (n = 26 and 927 for CEN-Y and Other CENs,

respectively). Dashed line indicates average of all centromeres.

CHAPTER 5

General Discussion;

Or,

What I’ve Learned and What I Have to Say about It

Dani L. Bodor


INTRODUCTION

In this thesis I have presented my work on quantitative aspects of human

centromere inheritance. Specifically, I have designed an algorithm to

automatically recognize centromeric foci on fluorescent micrographs and

quantify their signal intensity (Chapter 2). This algorithm was combined

with SNAP-based pulse-chase experiments to analyze regulatory factors of

CENP-A stability and assembly dynamics (Chapter 3). Furthermore, I have

used a related quantification strategy to determine the number of CENP-A

molecules at human centromeres and to elucidate the cell and chromatin

distribution of this most critical of centromere proteins (Chapter 4). The

previous chapters have detailed my specific methods and results. In this

chapter, I will discuss on a more conceptual level what my findings have to

offer to life, the universe, … and everything centromere biology-related.

Conclusions

217

NON-CENTROMERIC CENP-A

In 1985, a 17 kDa protein recognized by human auto-immune sera from

scleroderma patients was originally baptized as CENP-A (CENtromere

Protein A) for the single property of being centromere localized (Earnshaw

& Rothfield, 1985). While the essential role of CENP-A in centromere

function and specification is well established, in recent years, multiple

independent studies have found detectable levels of nucleosomal CENP-A

outside of centromeres in human cells (Hasson et al, 2013; Lacoste et al,

2014), as well as in other species (Camahort et al, 2009; Choi et al, 2012;

Shang et al, 2013). In fact, the centromeric pool represents less than a third

of all chromatin bound CENP-A (Figure 4.4) and approximately a fifth of the

total protein pool (Figure 4.3) in human RPE cells. Given this minority

population at the centromere, an extreme point of view would be that

‘centromere protein A’ is perhaps a misnomer for this particular protein.

However, there is a completely different way of seeing this. Alphoid

sequences represent only ~2.6% of the total human genome (Willard &

Waye, 1987; Hayden et al, 2013), and a large proportion of the α-satellite

DNA is devoid of CENP-A (Warburton et al, 1997; Spence et al, 2002;

Hayden et al, 2013). Indeed, one publication found that the CENP-A

enriched domain represents only 35-50% of the entire length of the

α-satellite repeats (Sullivan et al, 2011). Taking these numbers into account,

we determined that the centromeric minority (in absolute numbers) of

CENP-A represents a nearly 50-fold enrichment compared to the overall

genome when measured on a per nucleosome basis (Figure 4.8). Thus, given

that there is currently some debate in the field regarding the nomenclature

of this protein (Talbert et al, 2012; Earnshaw et al, 2013; Talbert & Henikoff,

2013; Earnshaw & Cleveland, 2013), I would like to take this opportunity to

suggest that it promptly be renamed to what is, strictly speaking, the most

accurate name: CENrichedP-A.

Chapter 5

218

In order to maintain this strong enrichment at centromeres, a specialized

loading pathway exists that specifically targets CENP-A to the correct locus.

HJURP is a CENP-A specific histone chaperone (Dunleavy et al, 2009; Foltz

et al, 2009; Shuaib et al, 2010) and assembly factor (Barnhart et al, 2011),

that binds to CENP-A through a number of residues lacking in other H3

variants (Hu et al, 2011; Bassett et al, 2012). Centromere recruitment of

HJURP depends on the Mis18 complex members Mis18α and Mis18β

(Barnhart et al, 2011; Wang et al, 2014), which are interdependent for

centromere targeting with M18BP1 (Fujita et al, 2007), which is in turn

recruited to centromeres through binding to CENP-C (Moree et al, 2011),

itself a direct binding partner of CENP-A (Carroll et al, 2010). The exact

nature and mechanisms by which these proteins are able to recruit each

other are still unclear and currently under intense investigation.

Nevertheless, it is clear that this this closed feedback loop is ultimately

responsible for maintaining a high degree of CENP-A enrichment at

centromeres.

On the flipside, at least 98% of the genome is non-centromeric, and

CENP-A is multiple orders of magnitude less abundant than other H3

variants1. Thus, while high specificity of HJURP to CENP-A is essential to

avoid sequestration by typical H3 variants, strict evasion of CENP-A by

other histone chaperones may not be of much consequence. Indeed, there

are indications that multiple assembly factors are capable of some degree of

CENP-A assembly into chromatin. First, when expressed from a typical H3.1

promoter, CENP-A is distributed throughout the nucleus and ceases to be

centromere enriched (Shelby et al, 1997). Similar findings were made upon

high levels of ectopic CENP-A overexpression from a constitutively active

promoter (Van Hooser et al, 2001; Gascoigne et al, 2011), but not upon

lower levels of overexpression (Shelby et al, 1997; Gascoigne et al, 2011;

1 This estimate is derived from my finding that there are <105 CENP-A molecules per RPE cell (Figure 4.2F), while there are ~3·107 nucleosome positions in a diploid human genome.

Conclusions

219

Figure 4.1C). More recently, direct evidence was found for crosstalk between

DAXX, a major histone H3.3 chaperone (Drané et al, 2010; Goldberg et al,

2010), and CENP-A, which were shown to be able to interact in vitro, albeit

with lower affinity than H3.3 (Lacoste et al, 2014). Moreover, upon CENP-A

overexpression, it becomes enriched at typical H3.3 sites in a DAXX

dependent manner and heterotypic CENP-A- and H3.3-containing

nucleosomes are observed (Lacoste et al, 2014). However, although a small

fraction of heterotypical CENP-A nucleosomes have been previously

reported upon overexpression in an independent study (Foltz et al, 2006),

they were not detected at wildtype expression levels and only minor co-

enrichment of CENP-A and H3.3 was observed (Lacoste et al, 2014).

Although CENP-A and H3.1 were not observed within a single nucleosome,

no careful analysis was performed regarding the potential interaction

between CENP-A and the canonical H3,1 assembly factor CAF (Lacoste et al,

2014). Thus, the restriction of CENP-A expression to G2 phase (Shelby et al,

1997, 2000), just prior to its loading in the beginning of the subsequent G1

(Jansen et al, 2007) and distinct from the major phase of canonical

nucleosome assembly (Worcel et al, 1978), may limit its potential for

misincoporation. Taken together, it appears that the correct (quantitative

and/or temporal) regulation of CENP-A expression is a major driving force

in preventing ectopic accumulation of CENP-A.

Although the majority of CENP-A is not centromere localized, I consider

the non-centromeric pool of this protein as noise. It would be difficult to

imagine an efficient mechanism with such a high degree of stringency that it

would ensure that >98% of the chromatin remains devoid of CENP-A.

Although only 20% of CENP-A is centromere localized (Figure 4.8), I would

not be surprised if the fraction of many other proteins that is active, or at

least present at the functionally relevant location, is similar or lower.

Importantly, although I would argue that it is unlikely that ectopic CENP-A

has a direct endogenous function, this does not exclude that it can influence

the regulation of non-centromeric chromatin. This may be especially

Chapter 5

220

relevant when CENP-A is overexpressed, as is the case in many cancer cells

(Lacoste et al, 2014; Thiru et al, 2014). Indeed, ectopically assembled

CENP-A has been shown to reduce CTCF occupancy at its typical binding

sites in both naturally overexpressing cancer cell lines and upon

experimentally induced CENP-A overproduction in HeLa cells (Lacoste et al,

2014). In addition, although direct evidence for a functional relationship

remains elusive and many results are somewhat ambiguous, a number of

studies have reported a link between non-centromeric CENP-A and DNA

damage response (Zeitlin et al, 2005, 2009, 2011; Ambartsumyan et al,

2010; Lacoste et al, 2014). Nevertheless, at wildtype expression levels,

CENP-A nucleosomes represent less than 0.1% of all non-centromeric

chromatin (Figure 4.8), indicating a minor effect, if any, on chromatin

(mis-) regulation.

Conclusions

221

THE ULTRASTABILITY OF CENP-A

It has become apparent over the last years that the chromatin dynamics

of CENP-A are unique among nucleosomes. Canonical H3.1 is assembled

throughout the genome during S phase, in a replication dependent manner

(Worcel et al, 1978; Ray-Gallet et al, 2011), while H3.3 is preferentially

assembled at specific loci throughout the cell cycle (Ahmad & Henikoff,

2002; Ray-Gallet et al, 2002, 2011; Goldberg et al, 2010). However,

assembly of centromeric CENP-A is restricted to a brief period in the cell

cycle, which in metazoans immediately follows mitotic exit (Jansen et al,

2007; Schuh et al, 2007; Bernad et al, 2011; Moree et al, 2011; Dunleavy et

al, 2012; Silva et al, 2012). CENP-A assembly is regulated, at least in part, by

phosphorylation of HJURP, the Mis18 complex, and itself by the key cell

cycle kinases Cdk1, Cdk2, and Plk1 (Silva et al, 2012; McKinley &

Cheeseman, 2014; Müller et al, 2014; Wang et al, 2014; Yu et al, 2015). In

addition to its atypical assembly dynamics, CENP-A also displays an

extreme level of chromatin maintenance, not observed for any other type of

nucleosome. Indeed, while canonical histones turn over with a half-life of

approximately 8 hours (Figure 3.3; Kimura & Cook, 2001), no turnover of

CENP-A was detected, apart from replicative dilution, for up to 5 days in

culture (Figures 3.3, 3.4, and 3.S3). However, the full mechanism leading to

CENP-A ultrastability, which may exceed that of any other protein in nature,

remains unclear.

Intrinsic determinants

One possibility is that long-term retention is conferred onto CENP-A

through a cis regulatory region that differs from other histone variants.

Consistent with this hypothesis, hydrogen/deuterium-exchange experiments

identified a region within the histone fold domain of CENP-A that induces

an increased conformational rigidity of the CENP-A/H4 binding interface as

compared to H3/H4 (Black et al, 2004, 2007a). This region, spanning loop1

and the α2-helix, was termed CENP-A targeting domain (CATD), because

Chapter 5

222

substitution of the 22 divergent amino acids into H3 induces a clear

enrichment of chimeric H3CATD histones at centromeres (Black et al, 2004).

Consistently, it was later shown that the CATD mediates recognition of

CENP-A by its assembly factor HJURP (Foltz et al, 2009; Shuaib et al, 2010;

Bassett et al, 2012). Moreover, H3CATD displays identical loading dynamics as

CENP-A (Figure 3.4A–B), arguing that the correct cell cycle regulation of

assembly acts upon its loading factors rather than upon CENP-A itself.

However, centromere enrichment appears not to be exclusively dependent

on binding to its chaperone, as specific residues of the CATD are required

for centromere accumulation but not for assembly at sites of ectopically

targeted HJURP (Bassett et al, 2012). Importantly, although not all

properties of CENP-A are reproduced after a clean genetic substitution by

H3CATD, which is insufficient to recruitment downstream centromere and

kinetochore proteins, it is capable to maintain its own centromeric levels

over many divisions (Fachinetti et al, 2013). Taken together, a model

emerges where the CATD is primarily responsible for maintaining

centromere identity, but not centromere function.

In addition to its regulatory role in CENP-A assembly, the CATD also

confers an increased nucleosome stability. SNAP-based pulse-chase

experiments show that the long-term retention of H3CATD at centromeres

approaches that of CENP-A (Figure 3.4E). One possibility is that the more

rigid nucleosome structure of in vitro assembled complexes conferred by the

CATD translates into an increase in protein stability in dividing cells.

Interestingly, although no effect was observed on chromatin assembly at

ectopic sites of HJURP tethering, conversion of six hydrophobic CATD

residues to their H3 counterpart, thought to revert the rigidity, caused a

severe defect in centromere accumulation (Bassett et al, 2012). Although

this observation could theoretically indicate a decreased stability of

otherwise properly assembled nucleosomes, it is unclear why the extent of

the defect would suggest an even lower retention than expected for

canonical H3 nucleosomes. An alternative interpretation is that this mutant

Conclusions

223

CENP-A is not properly targeted to centromeres, perhaps through HJURP-

independent regulation. In a separate study, CENP-A lacking a small (2

residue) protrusion in loop1 of the CATD that is not present in H3 was

cotransfected with wildtype protein, and it was found that the ratio of

mutant-to-wildtype CENP-A at centromeres decreases over time (Tachiwana

et al, 2011). Although the authors interpreted this result as a compromised

centromeric stability of the mutant protein, it is equally consistent with

other induced defects, e.g. mitotic arrest, conferring a growth disadvantage,

or being otherwise toxic to cells. While conclusive evidence regarding which

residues or subdomains of the CATD induce the increased nucleosome

stability is currently lacking, this may be provided by pulse-chase analysis of

SNAP-tagged mutant versions of CENP-A or H3CATD (Figures 2.2 and 3.4),

potentially in combination with LacO tethering of HJURP (Barnhart et al,

2011; Bassett et al, 2012).

External binding factors

Although ultrastability could be an intrinsic property of CENP-A, an

alternative possibility is that other proteins also contribute to its

centromeric retention. Interestingly, whereas the stability of H3CATD was not

statistically different than expected for replicative dilution, it does appear

slightly less stable than CENP-A (Figure 3.4). While it may be an artifact of

imperfect targeting of H3CATD to centromeres, this result does indicate that

introduction of the CATD may be insufficient to confer full ultrastability.

Moreover, the CATD may not have a direct effect on CENP-A maintenance,

but rather induce binding of other proteins that are responsible for its stable

retention. Thus, external factors could either (physically or functionally)

interact with the CATD or play an independent role to confer full stability.

An interesting hypothesis is that there is an overlap between CENP-A

assembly and maintenance factors. One indication for this is that a

proportion of HJURP interacts with chromatin incorporated CENP-A (Foltz

et al, 2006), although it is not clear what the functional relevance of this

Chapter 5

224

interaction is, if any. In addition, in one study, depletion of M18BP1 resulted

in a dramatic decrease of steady state CENP-A levels, beyond what would be

expected solely from a complete lack of nascent incorporation (Maddox et al,

2007). Nevertheless, I was able to exclude a role in CENP-A stability for

either of these proteins by depleting them in CENP-A-SNAP expressing cells

(Figures 3.5). Similarly, immunodepletion of HJURP from Xenopus extracts

did not affect the centromeric levels of CENP-A in arrested cells (Bernad et

al, 2011). Thus, despite a dependence on the CATD for both assembly and

maintenance, it appears that these represent separate properties of CENP-A

nucleosomes.

To my knowledge, only two external factors have been reported to play a

role in stable retention of CENP-A. The first is a group of proteins

constituting a small GTPase switch that is required to retain nascent

CENP-A at centromeres (Lagana et al, 2010). However, CENP-A that was

assembled prior to depletion of MgcRacGAP, a key regulator in this process,

remained unaffected (Lagana et al, 2010). Thus, it remains unclear whether

this protein is truly responsible for stabilizing CENP-A nucleosomes, or

perhaps somehow involved in the proper chromatin assembly of centromere

targeted (non-nucleosomal) CENP-A. Irrespectively, the contribution of this

GTPase switch to an effective CENP-A loading process appears to be higher

than to its long-term retention. Second, in a study performed in Xenopus

egg extracts, it was shown that depletion of condensins results in a reduction

of CENP-A from centromeres of non-dividing cells (Bernad et al, 2011).

Condensins are known to be important regulators of chromosome

organization and their depletion would be expected to considerably

influence the structure of (centromeric) chromatin (Hagstrom et al, 2002;

Wignall et al, 2003; Oliveira et al, 2005). Although this hints at a functional

relationship between condensin and CENP-A stability, quantification of the

affected chromatin may be confounded by potential artifacts of these

immunodepletion experiments, such as defocussing of centromeric signals

or an altered antibody accessibility to CENP-A. To control for this potential

Conclusions

225

artifact, fluorescently tagged CENP-A could be used or counterstaining

could be performed with an antibody against another centromere protein

that would not be expected to be influenced by loss of CENP-A.

Nevertheless, although it will be important to address the issue raised above,

condensins remain among the strongest candidate CENP-A maintenance

factors identified to date.

Members of the constitutive centromere associated network (CCAN)

form yet another group of candidate proteins involved in CENP-A retention.

A decrease of centromeric CENP-A levels has been observed after depletion

of a number of CCAN members, including CENP-H (Okada et al, 2006,

2009), CENP-N (Carroll et al, 2009), and CENP-C (Carroll et al, 2010). In

addition, CENP-A can directly bind to both CENP-N (Carroll et al, 2009)

and CENP-C (Carroll et al, 2010; Guse et al, 2011; Kato et al, 2013), through

the CATD and C-terminal six residues (LEEGLG), respectively. It must be

noted, however, that reconstitution experiments in Xenopus egg extracts

indicate that recruitment of CENP-N is independent of the CATD, but

depends exclusively on CENP-C (Guse et al, 2011), and it thus remains

unclear what the functional relevance is of the direct interaction between

CENP-A and CENP-N. Interestingly, while both CENP-C and CENP-N turn

over at the centromere throughout most of the cell cycle, they become stably

bound during mid–late S phase and their centromeric levels increase

(Hemmerich et al, 2008; Hellwig et al, 2011; Gascoigne & Cheeseman,

2013). These specific cell cycle dynamics are somewhat suggestive for a role

in CENP-A retention, because chromatin disruption by the replication

machinery is one of the most challenging processes for nucleosome

retention (Groth et al, 2007; Alabert & Groth, 2012) and centromeres have

been shown to be relatively late replicating domains (O’Keefe et al, 1992;

Shelby et al, 2000). Indeed, our preliminary experiments indicate that

depletion of CENP-C results in a slightly accelerated loss of pre-incorporated

centromeric CENP-A (Figure 3.A). Although CENP-N was previously shown

to play a role in the CENP-A assembly pathway (Carroll et al, 2009), we did

Chapter 5

226

not observe any defect on either loading or maintenance after RNAi against

CENP-N (data not shown). However, it must be noted that we did not

carefully monitor the extent of protein depletion, which limits the

interpretability of our results. Therefore, both CENP-N and, especially,

CENP-C remain strong candidate CENP-A maintenance factors.

Open questions regarding CENP-A ultrastability

As discussed above, there is evidence for both intrinsic and external

contributions to the lack of CENP-A turnover. However, a number of

interesting considerations regarding the nature of CENP-A ultrastability

remain unanswered. First, it would be important to assess whether this

protein is equally stable at non-centromeric loci as at the centromere, which

will help identify regulatory processes of CENP-A maintenance. In addition,

long-term retention assays have currently only been performed on human

tissue culture cells and it remains unknown whether CENP-A ultrastability

is specific to this system, or is conserved in other organisms as well.

Interestingly, there is at least one known example of epigenetically defined

centromeres where this protein is not stably retained between divisions,

since it was shown that the entire pool of CENP-AHCP-3 turns over between

the first and second mitotic division in C. elegans embryogenesis

(Gassmann et al, 2012). However, C. elegans may be an exception, not only

because of the holocentric nature of their chromosomes (Albertson &

Thomson, 1982), but also because CENP-AHCP-3 is lost completely during

gametogenesis and is therefore not absolutely required to specify

centromeric identity (Monen et al, 2005; Gassmann et al, 2012). Conversely,

in most species analyzed, CENP-A can be readily detected in both mature

sperm (Palmer et al, 1990, 1991; Bernad et al, 2011; Dunleavy et al, 2012;

Raychaudhuri et al, 2012; Chmátal et al, 2014) and oocytes (Dunleavy et al,

2012; Chmátal et al, 2014), and it has been shown that Drosophila

CENP-ACID is required in sperm cells to specify centromeres on paternally

inherited chromosomes of the next generation (Raychaudhuri et al, 2012).

Conclusions

227

Finally, we do not currently know what the dynamics of centromeric

CENP-A are in long-lived post-mitotic cells such as neurons or human

oocytes, which can remain arrested in meiotic prophase I for decades. To my

knowledge, the only known analysis in this direction was performed on

human pancreatic tissue, where it appears that centromeric CENP-A

declines with age in non-dividing islet cells, but not in actively dividing

exocrine cells (Lee et al, 2010). Although the results are intriguing, this

study in a small number of human samples does not have the power to

interrogate the molecular mechanisms of CENP-A turnover dynamics and it

would be important to revisit these findings in a more amenable model.

Moreover, while retention of CENP-A in post-mitotic pancreatic cells may

not be essential, oocytes need to reenter the cell cycle upon fertilization and

thus need to preserve functional centromeres. Indeed, in one study, non-

canonical regulation of CENP-ACID assembly has been observed during both

male and female meiosis in Drosophila (Dunleavy et al, 2012), although in

an accompanying paper no meiotic loading was detected during

spermatogenesis in this species (Raychaudhuri et al, 2012). In conclusion,

although progress is being made towards understanding the regulation of

CENP-A ultrastability, there is still a long way to go.

Chapter 5

228

MASS ACTION VERSUS ULTRASTABILITY

Mass action mechanisms were first described 150 years ago to explain

how reversible chemical reactions ultimately result in a dynamic equilibrium

(Waage & Gulberg, 1864). According to this theory, the output of a chemical

reaction is directly proportional to its input, i.e. the amount of product

formed depends directly on the amount of reactants added, and is dictated

by the rate constants of the reaction (Guldberg & Waage, 1867). A similar

relationship is observed for CENP-A, where the centromeric pool is

maintained in direct proportion to varying total cellular levels (Figure 4.1).

This observation argues that there is a fixed centromere targeting efficiency

of CENP-A, which is independent of the amount of protein present.

However, given the ultrastable maintenance of CENP-A at centromeres (see

above) as opposed to a dynamic equilibrium, this regulation does not follow

the same principles as a mass action mechanism.

In fact, three modes of regulating CENP-A inheritance have been shown

to exist. These are: 1) No exchange between non-centromeric and

centromeric CENP-A pools (Figure 3.4D; Hemmerich et al, 2008); 2)

stochastic redistribution of existing centromeric CENP-A over two

centromeres during each division (Figure 4.5C); and 3) assembly of nascent

CENP-A in direct proportion to the total cellular pool (Figure 4.1). However,

if there is no form of communication between the centromeric and non-

centromeric pool, individual centromeres would have the potential of

reaching extreme values, which would lead to an increasing variance of

CENP-A with each round of dilution and replenishment. Thus, the absence

of a true mass action mechanism appears inconsistent with a fixed ratio of

total-to-centromeric CENP-A.

Conclusions

229

Figure 5.1 Hypothetical scenario of density dependent CENP-A assembly. While, exclusive positive or negative

feedback of CENP-A levels on incorporation of nascent protein would either lead to centromere spreading or centromere

extinction, a combination of switch-like positive (green) and linear negative (red) regulation of CENP-A assembly would

explain the observed maintenance of CENP-A levels. Similarly, several rules are required to properly regulate complex

behavior of kinds as well (God, 1448BC). In the system described above, optimal loading efficiency is reached at

intermediate densities (average centromeric CENP-A occupancy: ~4%; see Chapter 4), while virtually no loading occurs

at very low levels of CENP-A, as found in generic chromatin (~0.1% occupancy; see Chapter 4), and efficiency is

decreased at centromeres with a very high CENP-A occupancy. Red and grey nucleosomes represent CENP-A and H3

nucleosomes, respectively.

Chapter 5

230

One trivial solution to this paradox could be that cells that have exceeded

certain boundaries are eliminated from the population. This would not

require any additional CENP-A regulation, but rather a process that reacts to

extreme levels. Theoretically, this could be a passive process: e.g. too little or

too much CENP-A would lead to a dysfunctional centromere, which in turn

leads to chromosomal instability and, ultimately, cell death. However, this

would likely not be a very effective mechanism, as a low level of

chromosomal instability and aneuploidy is generally tolerated by cells

(Holland & Cleveland, 2009). Alternatively, a hypothetical monitoring factor

could exist, which actively drives cells into programmed cell death upon

extreme high or low CENP-A levels. Irrespective of the nature of the

mechanism that eliminates cells with extreme levels, the variance of

CENP-A would need to be kept to a minimum to avoid losing a large

proportion of cells from the population.

An alternative hypothesis is that there is an additional, yet to be

discovered form of regulating centromeric CENP-A levels. Indeed, although

the efficiency of CENP-A assembly is constant on the cellular scale, it could

be regulated on the per-centromere level. Specifically, the pre-incorporated

pool of CENP-A would be expected to negatively influence targeting of

nascent protein. However, this hypothesis is apparently at odds with the fact

that CENP-A is predominantly assembled at existing centromeres, which

inherently have a higher density of CENP-A than non-centromeric loci.

Thus, two opposing forces may be required to accurately regulate CENP-A

levels. First, a positive regulator of CENP-A recruitment that has an almost

all-or-nothing effect (Figure 5.1, green) is necessary, thus generating a

minimal CENP-A threshold. Next, negative regulation would be required,

the strength of which is expected to correlate with the amount of CENP-A

(Figure 5.1, red). Combined, these processes would lead to the mass action

type of regulation observed for maintenance of stably bound CENP-A levels

(Figure 5.1).

Conclusions

231

Although it is not evident what these regulators would be, some

candidates come to mind. Regarding positive regulation, it is likely that a

high enough density of CENP-A creates a platform that is recognized as a

centromere. In this case, the actual CENP-A level is ir relevant, as long as a

certain threshold is exceeded. Indeed, I found that neither CENP-C nor

CENP-T centromere levels correlate with CENP-A levels (Figure 4.6A) and a

similar effect was seen for CENP-I (Liu et al, 2006). Of these CCAN

members, CENP-C is an especially good candidate, as it has been proposed

to recruit M18BP1 to centromeres (Moree et al, 2011; Dambacher et al,

2012). As opposed to the switch-like positive regulation, negative feedback is

more likely to be linear with CENP-A levels. Thus, good candidates would be

proteins that are stoichiometric and/or cosegregate with CENP-A, such as

its proposed direct binding partner CENP-N (Carroll et al, 2009), or perhaps

even (PTMs on) CENP-A itself. A similar hypothesis has been put forward

previously, wherein microtubule-generated tension on centromeres is

proportional to mitotic CENP-A levels and negatively influences assembly of

nascent CENP-A in the subsequent G1 (Brown & Xu, 2009). Because the

amount of CENP-A available for centromere assembly may still correlate

with total protein levels in the absence of a negative regulator, assays to

identify such a factor would likely need to focus on deregulated variances

rather than mean CENP-A values. Together, switch-like recruitment of a

positive regulator and stoichiometric recruitment of an antagonist assembly

would lead to stable maintenance of steady state CENP-A levels.

Above, I have presented two potential solutions to the paradoxical

observations regarding the regulation of centromeric CENP-A levels.

However, both are quite speculative and complex in nature and no evidence

exists for either. Nevertheless, it is a well-documented fact that some people

can believe as many as six impossible things before breakfast (Carroll, 1871).

Thus, although a more realistic hypothesis would be preferable, mine also

remain plausible.

Chapter 5

232

THE CRITICAL AMOUNT OF CENP-A

Chapter 4 of this thesis presents an analysis of the amount of CENP-A on

human centromeres. In addition, initial characterizations were made of cells

with varying amounts of CENP-A. The next important goal, which lies at the

heart of understanding the epigenetic mechanism driving centromere

inheritance, is to determine the minimum amount of CENP-A required to

define a centromere. Unfortunately, however, I was not able to resolve this

within the timeframe of my PhD. Nevertheless, I will discuss my ideas

regarding the critical amount of CENP-A, including hints from the published

literature as well as potential methods to address this experimentally.

CENP-A variance

The amount of CENP-A on human centromeres varies at different levels.

First, not all centromeres of one cell have the same amount of CENP-A.

Although there may be some contribution of centromere specific differences

(Figure 4.7C–F), 85% cells analyzed passed a normality test2, consistent

with a largely stochastic nature of intracellular variability. Second, variation

observed between cell averages (Figure 4.2C) is also likely to be stochastic,

as all seven datasets (experiments) presented in this figure passed the

normality test. Finally, substantial variation is observed between cultured

cell lines (Figure 4.7H), which may represent differential expression levels of

e.g. CENP-A itself, its loading, and/or other regulatory factors. These

differences may have emerged during the production or in vitro evolution of

the cell lines presented, although a contribution of cell type specific

differences may exist, which has to my knowledge not been addressed for

normal human tissues. This variance of CENP-A levels is an important issue

to take into consideration when determining the critical amount of CENP-A.

2 The distribution of centromeric CENP-A levels of 94 of the 111 mitotic spreads presented in Figure 4.7S1 passed a D'Agostino & Pearson omnibus normality test using GraphPad Prism (α=0.05). This particular dataset was chosen to test for normality because clustering of multiple centromeres into a single spot is excluded and because at least 23 centromeres were measured in each cell.

Conclusions

233

Centromere maintenance

Average mitotic centromeres in wildtype RPE cells contain ~200

molecules of CENP-A (Figure 4.8). However, at least two results show that

lower levels are sufficient to maintain centromere identity. First is the

finding that DLD-1 cells, a cultured colorectal adenocarcinoma cell line, have

on average only ~25% as much CENP-A as RPE cells (Figure 4.7H).

Evidently, it is possible, perhaps even likely, that this level of CENP-A leads

to (mitotic) defects such as chromosome missegregation or centromere loss.

Nevertheless, this clearly demonstrates that 50 CENP-A molecules are more

than sufficient to stably sustain centromeric identity throughout

generations. The second analysis was performed on an RPE cell line in

which the CENP-A gene has been flanked by LoxP sites, allowing for its

controlled deletion from the genome (Fachinetti et al, 2013). Following Cre-

mediated gene ablation in these cells, stable retention of existing

centromeric CENP-A molecules leads to a 50% decrease per division.

Surprisingly, although the mitotic fidelity was compromised, cell duplication

rates remained unaffected for at least 5 days after deletion of CENP-A, at

which point the average centromeric levels were down to ~7% (Fachinetti et

al, 2013). Similar results were obtained in HeLa cells, where the recruitment

of a number of centromere proteins remained unaffected in cells where

CENP-A levels had been depleted by RNAi to ~10% (Liu et al, 2006). These

results argue that, although low levels of CENP-A affect centromere

function, 14 molecules may be sufficient to maintain centromere identity.

However, an alternative hypothesis could be that for a limited number of

divisions, centromeres can survive independently of CENP-A, perhaps

through semi-stable self-regulated recruitment of downstream CCAN

proteins. Taken together, these results argue that in typical human cells the

number of centromeric CENP-A molecules is substantially higher than the

critical amount required for epigenetic centromere maintenance.

Chapter 5

234

Determining the true minimum amount of CENP-A required for

centromere maintenance is not an easy feat to accomplish. For this, it would

be necessary to differentially manipulate CENP-A levels, ideally in a well

regulated and acute manner. One possibility would be to stably decrease

CENP-A levels by genomic integration of an shRNA cassette (Black et al,

2007b) and selecting for cells that maintain viability with minimal protein

levels. However, this approach is likely susceptible to a large degree of

variation of knockdown efficiency, even in clonal cell lines. An alternative

would be to use a similar system to the conditional knock-out cells of

Fachinetti et al, but containing an ectopic CENP-A gene under the control of

a regulatable promoter. In this case, CENP-A expression can either be

maintained at differential levels or perhaps be reinitiated at different time

intervals after deletion of the endogenous gene to determine at what point

centromeric levels drop below a critical threshold. Another option would be

to take advantage of a previously developed system where CENP-A is fused

to the AID tag, which allows for inducible proteasome mediated degradation

within a few hours after addition of a cell exogenous hormone (Holland et al,

2012). This system may allow for the determination of the minimum amount

of CENP-A, either by washing out the inducing agent prior to complete

degradation, or by co-expression of unresponsive CENP-A at differential

levels (e.g. using promoters of different strength). However, a confounding

factor of any of these approaches is that all centromeres are affected

simultaneously, making it difficult to determine the minimum amount of

CENP-A on any surviving centromere is. One method that could potentially

0vercome this drawback is chromophore-assisted laser inactivation (CALI),

which applies photosensitive molecules that produce reactive oxygen species

(ROS) upon light induction to selectively destroy specific proteins at high

spatial resolution (Jay, 1988; Liao et al, 1994; Wang et al, 1996). Effective,

genetically encoded photosensitizer protein tags have been developed

(Bulina et al, 2006; Takemoto et al, 2013), which can be fused to target

proteins such as CENP-A and allow for its selective destruction from

Conclusions

235

individual centromeres. However, one drawback of CALI is that it is not as

well established as many other lab techniques and experiments may suffer

from unanticipated obstacles. Taken together, complex experiments will be

inevitable to determine the critical amount of CENP-A for centromere

maintenance. Nevertheless, these experiments should be pursued, as a

successful assay will provide fundamental insights regarding the epigenetic

nature of centromere inheritance.

De novo centromere formation

There is an inherent conflict between a high and low critical amount of

CENP-A to specify exactly one centromeric locus per chromosome. On the

one hand, a low threshold decreases the chance of losing a centromere due

to stochastic redistribution, while on the other hand it increases the chance

of forming an additional centromere on an ectopic locus due to random

accumulation. Interestingly, however, differences exist between the

processes of centromere maintenance and centromere formation. One clear

example of this is the differential role of CENP-B, which is essential for de

novo centromere formation on human artificial chromosomes (Ohzeki et al,

2002). Conversely, this protein is dispensable for maintenance of existing

centromeres, as evidenced by knock-out mice, which are perfectly viable,

reproductively normal, and do not show any mitotic or meiotic

abnormalities (Hudson et al, 1998). Similarly, the minimum amount of

CENP-A to maintain an existing centromere may differ from the critical

amount required to initiate a centromere on a naïve chromatin domain.

It is difficult to estimate from the existing literature how much CENP-A

is required for de novo centromere formation. Stable, self-sustaining

neocentromeres have been produced experimentally using a number of

methods. One example is human artificial chromosomes, which are

produced by introducing large fragments of alphoid DNA (~60–70 kb) into

cells and selecting for their retention (Ikeno et al, 1998; Ohzeki et al, 2002,

2012). Alternatively, centromeres of existing chromosomes have been

Chapter 5

236

deleted, which allowed for the isolation of clones containing neocentromeres

on a ectopic sites in fission yeast (Ishii et al, 2008), Candida albicans (Ketel

et al, 2009), or chicken DT40 cells (Shang et al, 2013). Moreover, self-

sustaining centromeres can be induced by tethering CENP-A to a LacO array

in Drosophila S2 cells (Mendiburo et al, 2011) or tethering of HJURP,

CENP-C, or CENP-I to acentric chromosomes of chicken DT40 cells (Hori et

al, 2013). However, in none of these cases was there control or measurement

of the amount of CENP-A recruited, especially in the initial phase of

centromere formation.

Determining the critical amount of CENP-A required for de novo

centromere formation would ideally involve the recruitment of a controlled

number of molecules to a naïve site. One option would be to tether CENP-A

(or HJURP) to LacO arrays of different sizes and determine what the

smallest number of binding sites is that can initiate a centromere. A similar,

yet slightly more elegant strategy would be to take advantage of the CRISPR

system, which allows for targeting of fusion proteins to unique loci by using

guide RNAs that complement genomic sequences (Chen et al, 2013; Qi et al,

2013). Using multiple guide RNAs to target CENP-A to neighboring sites

would in principle allow for the titration of the minimum amount required

to initiate centromere formation. Moreover, this system could be used to

determine both the ideal distribution of CENP-A (high density in a small

region or lower density in a slightly larger domain) as well as the role of the

genomic context (transcriptional activity, histone modification density, etc.)

on the efficiency of neocentromere formation. Thus, an effective CRISPR-

mediated de novo centromere formation assay would be instrumental in

answering many open questions regarding the processes leading to

neocentromere formation.

Conclusions

237

CONCLUDING REMARK

Centromeres have intrigued cell biologists for over a century. Since their

first description by Walther Flemming (1880), a great deal has been

discovered regarding the function and nature of centromeres. Key

discoveries include their multiple regulatory roles ensuring accurate

chromosome segregation, as well as their epigenetic mode of inheritance. I

myself have also made a contribution to our understanding of centromere

inheritance. Nevertheless, many key questions remain unanswered. Some of

these have been discussed in detail earlier in this chapter, including why a

substantial proportion of CENP-A is non-centromeric, how CENP-A protein

can be indefinitely retained at centromeres, how centromeric levels are

accurately maintained, and what the minimal amount of CENP-A to specify

centromere identity is. Other intriguing questions include how it is ensured

that there is exactly one centromere per chromosome and how centromeric

loci are accurately maintained in the apparent absence of physical

boundaries. Taken together, the centromere field still has a long way to go

and may provide enough study material to keep us going for another

hundred years.

Chapter 5

238

REFERENCES

Ahmad K & Henikoff S (2002) Histone H3 variants specify modes of chromatin assembly. Proc. Natl. Acad. Sci. U. S. A. 99: 16477–16484

Alabert C & Groth A (2012) Chromatin replication and epigenome maintenance. Nat. Rev. Mol. Cell Biol. 13: 153–167

Albertson DG & Thomson JN (1982) The kinetochores of Caenorhabditis elegans. Chromosoma 86: 409–428

Ambartsumyan G, Gill RK, Perez SD, Conway D, Vincent J, Dalal Y & Clark AT (2010) Centromere protein A dynamics in human pluripotent stem cell self-renewal, differentiation and DNA damage. Hum. Mol. Genet. 19: 3970–3982







Brown WRA & Xu Z (2009) The ‘kinetochore maintenance loop’—The mark of regulation? BioEssays 31: 228–236

Bulina ME, Chudakov DM, Britanova OV, Yanushevich YG, Staroverov DB, Chepurnykh TV, Merzlyak EM, Shkrob MA, Lukyanov S & Lukyanov KA (2006) A genetically encoded photosensitizer. Nat. Biotechnol. 24: 95–99




Conclusions

239

Carroll L (1871) Through the Looking-Glass, and What Alice Found There. London, England: Macmillan

Chen B, Gilbert LA, Cimini BA, Schnitzbauer J, Zhang W, Li G-W, Park J, Blackburn EH, Weissman JS, Qi LS & Huang B (2013) Dynamic Imaging of Genomic Loci in Living Human Cells by an Optimized CRISPR/Cas System. Cell 155: 1479–1491

Chmátal L, Gabriel SI, Mitsainas GP, Martínez-Vargas J, Ventura J, Searle JB, Schultz RM & Lampson MA (2014) Centromere Strength Provides the Cell Biological Basis for Meiotic Drive and Karyotype Evolution in Mice. Curr. Biol. 24: 2295–2300

Choi ES, Strålfors A, Catania S, Castillo AG, Svensson JP, Pidoux AL, Ekwall K & Allshire RC (2012) Factors That Promote H3 Chromatin Integrity during Transcription Prevent Promiscuous Deposition of CENP-ACnp1 in Fission Yeast. PLoS Genet 8: e1002985

Dambacher S, Deng W, Hahn M, Sadic D, Fröhlich J, Nuber A, Hoischen C, Diekmann S, Leonhardt H & Schotta G (2012) CENP-C facilitates the recruitment of M18BP1 to centromeric chromatin. Nucleus 3: 101–110

Drané P, Ouararhni K, Depaux A, Shuaib M & Hamiche A (2010) The death-associated protein DAXX is a novel histone chaperone involved in the replication-independent deposition of H3.3. Genes Dev. 24: 1253–1265

Dunleavy EM, Beier NL, Gorgescu W, Tang J, Costes SV & Karpen GH (2012) The Cell Cycle Timing of Centromeric Chromatin Assembly in Drosophila Meiosis Is Distinct from Mitosis Yet Requires CAL1 and CENP-C. PLoS Biol 10: e1001460


Earnshaw WC, Allshire RC, Black BE, Bloom K, Brinkley BR, Brown W, Cheeseman IM, Choo KHA, et al (2013) Esperanto for histones: CENP-A, not CenH3, is the centromeric histone H3 variant. Chromosome Res. 21: 101–106

Earnshaw WC & Cleveland DW (2013) CENP-A and the CENP nomenclature: response to Talbert and Henikoff. Trends Genet. TIG 29: 500–502

Earnshaw WC & Rothfield N (1985) Identification of a family of human centromere proteins using autoimmune sera from patients with scleroderma. Chromosoma 91: 313–321


Flemming W (1880) Beiträge zur Kenntniss der Zelle und ihrer Lebenserscheinungen. Theil II. Arch. Für Mikrosk. Anat. 18: 151–259


Chapter 5

240



Gascoigne KE & Cheeseman IM (2013) CDK-dependent phosphorylation and nuclear exclusion coordinately control kinetochore assembly state. J. Cell Biol. 201: 23–32


Gassmann R, Rechtsteiner A, Yuen KW, Muroyama A, Egelhofer T, Gaydos L, Barron F, Maddox P, et al (2012) An inverse relationship to germline transcription defines centromeric chromatin in C. elegans. Nature 484: 534–537

God (יהוה) (1448BC) Decalogue. 2nd ed. Mount Sinai: Moses

Goldberg AD, Banaszynski LA, Noh K-M, Lewis PW, Elsaesser SJ, Stadler S, Dewell S, Law M, et al (2010) Distinct factors control histone variant H3.3 localization at specific genomic regions. Cell 140: 678–691

Groth A, Rocha W, Verreault A & Almouzni G (2007) Chromatin challenges during DNA replication and repair. Cell 128: 721–733

Guldberg CM & Waage P (1867) Études sur les affinités chimiques. Brøgger & Christie


Hagstrom KA, Holmes VF, Cozzarelli NR & Meyer BJ (2002) C. elegans condensin promotes mitotic chromosome architecture, centromere organization, and sister chromatid segregation during mitosis and meiosis. Genes Dev. 16: 729–742


Hayden KE, Strome ED, Merrett SL, Lee H-R, Rudd MK & Willard HF (2013) Sequences Associated with Centromere Competency in the Human Genome. Mol. Cell. Biol. 33: 763–772

Hellwig D, Emmerth S, Ulbricht T, Döring V, Hoischen C, Martin R, Samora CP, McAinsh AD, Carroll CW, Straight AF, Meraldi P & Diekmann S (2011) Dynamics of CENP-N kinetochore binding during the cell cycle. J. Cell Sci. 124: 3871–3883


Holland AJ & Cleveland DW (2009) Boveri revisited: chromosomal instability, aneuploidy and tumorigenesis. Nat. Rev. Mol. Cell Biol. 10: 478–487

Conclusions

241

Holland AJ, Fachinetti D, Han JS & Cleveland DW (2012) Inducible, reversible system for the rapid and complete degradation of proteins in mammalian cells. Proc. Natl. Acad. Sci. 109: E3350–E3357

Van Hooser AA, Ouspenski II, Gregson HC, Starr DA, Yen TJ, Goldberg ML, Yokomori K, Earnshaw WC, Sullivan KF & Brinkley BR (2001) Specification of kinetochore-forming chromatin by the histone H3 variant CENP-A. J. Cell Sci. 114: 3529–3542


Hudson DF, Fowler KJ, Earle E, Saffery R, Kalitsis P, Trowell H, Hill J, Wreford NG, et al (1998) Centromere Protein B Null Mice are Mitotically and Meiotically Normal but Have Lower Body and Testis Weights. J. Cell Biol. 141: 309–319

Hu H, Liu Y, Wang M, Fang J, Huang H, Yang N, Li Y, Wang J, Yao X, Shi Y, Li G & Xu R-M (2011) Structure of a CENP-A-histone H4 heterodimer in complex with chaperone HJURP. Genes Dev. 25: 901–906

Ikeno M, Grimes B, Okazaki T, Nakano M, Saitoh K, Hoshino H, McGill NI, Cooke H & Masumoto H (1998) Construction of YAC–based mammalian artificial chromosomes. Nat. Biotechnol. 16: 431–439

Ishii K, Ogiyama Y, Chikashige Y, Soejima S, Masuda F, Kakuma T, Hiraoka Y & Takahashi K (2008) Heterochromatin Integrity Affects Chromosome Reorganization After Centromere Dysfunction. Science 321: 1088–1091


Jay DG (1988) Selective destruction of protein function by chromophore-assisted laser inactivation. Proc. Natl. Acad. Sci. 85: 5454–5458

Kato H, Jiang J, Zhou B-R, Rozendaal M, Feng H, Ghirlando R, Xiao TS, Straight AF & Bai Y (2013) A Conserved Mechanism for Centromeric Nucleosome Recognition by Centromere Protein CENP-C. Science 340: 1110–1113

Ketel C, Wang HSW, McClellan M, Bouchonville K, Selmecki A, Lahav T, Gerami-Nejad M & Berman J (2009) Neocentromeres Form Efficiently at Multiple Possible Loci in Candida albicans. PLoS Genet 5: e1000400



Lagana A, Dorn JF, De Rop V, Ladouceur A-M, Maddox AS & Maddox PS (2010) A small GTPase molecular switch regulates epigenetic centromere maintenance by stabilizing newly incorporated CENP-A. Nat. Cell Biol. 12: 1186–1193

Chapter 5

242

Lee S-H, Itkin-Ansari P & Levine F (2010) CENP-A, a protein required for chromosome segregation in mitosis, declines with age in islet but not exocrine cells. Aging 2: 785

Liao JC, Roider J & Jay DG (1994) Chromophore-assisted laser inactivation of proteins is mediated by the photogeneration of free radicals. Proc. Natl. Acad. Sci. 91: 2659–2663



McKinley KL & Cheeseman IM (2014) Polo-like Kinase 1 Licenses CENP-A Deposition at Centromeres. Cell 158: 397–411


Monen J, Maddox PS, Hyndman F, Oegema K & Desai A (2005) Differential role of CENP-A in the segregation of holocentric C. elegans chromosomes during meiosis and mitosis. Nat. Cell Biol. 7: 1248–1255

Moree B, Meyer CB, Fuller CJ & Straight AF (2011) CENP-C recruits M18BP1 to centromeres to promote CENP-A chromatin assembly. J. Cell Biol. 194: 855–871

Müller S, Montes de Oca R, Lacoste N, Dingli F, Loew D & Almouzni G (2014) Phosphorylation and DNA Binding of HJURP Determine Its Centromeric Recruitment and Function in CenH3CENP-A Loading. Cell Rep. 8: 190–203

Ohzeki J, Bergmann JH, Kouprina N, Noskov VN, Nakano M, Kimura H, Earnshaw WC, Larionov V & Masumoto H (2012) Breaking the HAC Barrier: histone H3K9 acetyl/methyl balance regulates CENP-A assembly. EMBO J. 31: 2391–2402



Okada M, Okawa K, Isobe T & Fukagawa T (2009) CENP-H–containing complex facilitates centromere deposition of CENP-A in cooperation with FACT and CHD1. Mol. Biol. Cell 20: 3986–3995

O’Keefe RT, Henderson SC & Spector DL (1992) Dynamic organization of DNA replication in mammalian cell nuclei: spatially and temporally defined replication of chromosome-specific alpha-satellite DNA sequences. J. Cell Biol. 116: 1095–1110

Oliveira RA, Coelho PA & Sunkel CE (2005) The condensin I subunit Barren/CAP-H is essential for the structural integrity of centromeric heterochromatin during mitosis. Mol. Cell. Biol. 25: 8971–8984

Conclusions

243

Palmer DK, O’Day K & Margolis RL (1990) The centromere specific histone CENP-A is selectively retained in discrete foci in mammalian sperm nuclei. Chromosoma 100: 32–36


Qi LS, Larson MH, Gilbert LA, Doudna JA, Weissman JS, Arkin AP & Lim WA (2013) Repurposing CRISPR as an RNA-Guided Platform for Sequence-Specific Control of Gene Expression. Cell 152: 1173–1183



Ray-Gallet D, Woolfe A, Vassias I, Pellentz C, Lacoste N, Puri A, Schultz DC, Pchelintsev NA, Adams PD, Jansen LET & Almouzni G (2011) Dynamics of histone H3 deposition in vivo reveal a nucleosome gap-filling mechanism for H3.3 to maintain chromatin integrity. Mol. Cell 44: 928–941


Shang W-H, Hori T, Martins NMC, Toyoda A, Misu S, Monma N, Hiratani I, Maeshima K, Ikeo K, Fujiyama A, Kimura H, Earnshaw WC & Fukagawa T (2013) Chromosome engineering allows the efficient isolation of vertebrate neocentromeres. Dev. Cell 24: 635–648

Shelby RD, Monier K & Sullivan KF (2000) Chromatin assembly at kinetochores is uncoupled from DNA replication. J. Cell Biol. 151: 1113–1118

Shelby RD, Vafa O & Sullivan KF (1997) Assembly of CENP-A into centromeric chromatin requires a cooperative array of nucleosomal DNA contact sites. J. Cell Biol. 136: 501–513



Spence JM, Critcher R, Ebersole TA, Valdivia MM, Earnshaw WC, Fukagawa T & Farr CJ (2002) Co‐localization of centromere activity, proteins and topoisomerase II within a subdomain of the major human X α‐satellite array. EMBO J. 21: 5269–5280

Sullivan LL, Boivin CD, Mravinac B, Song IY & Sullivan BA (2011) Genomic size of CENP-A domain is proportional to total alpha satellite array size at human

Chapter 5

244

centromeres and expands in cancer cells. Chromosome Res. Int. J. Mol. Supramol. Evol. Asp. Chromosome Biol. 19: 457–470


Takemoto K, Matsuda T, Sakai N, Fu D, Noda M, Uchiyama S, Kotera I, Arai Y, et al (2013) SuperNova, a monomeric photosensitizing fluorescent protein for chromophore-assisted light inactivation. Sci. Rep. 3: 2629

Talbert PB, Ahmad K, Almouzni G, Ausió J, Berger F, Bhalla PL, Bonner WM, Cande WZ, et al (2012) A unified phylogeny-based nomenclature for histone variants. Epigenetics Chromatin 5: 7

Talbert PB & Henikoff S (2013) Phylogeny as the basis for naming histones. Trends Genet. 29: 499–500

Thiru P, Kern DM, McKinley KL, Monda JK, Rago F, Su K-C, Tsinman T, Yarar D, Bell GW & Cheeseman IM (2014) Kinetochore genes are coordinately up-regulated in human tumors as part of a FoxM1-related cell division program. Mol. Biol. Cell 25: 1983–1994

Waage P & Gulberg CM (1864) Studier over Afiniteten. Forh. Vidensk.-Selsk. Christiania: 35–45

Wang F-S, Wolenski JS, Cheney RE, Mooseker MS & Jay DG (1996) Function of Myosin-V in Filopodial Extension of Neuronal Growth Cones. Science 273: 660–663

Wang J, Liu X, Dou Z, Chen L, Jiang H, Fu C, Fu G, Liu D, et al (2014) Mitotic Regulator Mis18β Interacts with and Specifies the Centromeric Assembly of Molecular Chaperone Holliday Junction Recognition Protein (HJURP). J. Biol. Chem. 289: 8326–8336

Warburton PE, Cooke CA, Bourassa S, Vafa O, Sullivan BA, Stetten G, Gimelli G, Warburton D, Tyler-Smith C, Sullivan KF, Poirier GG & Earnshaw WC (1997) Immunolocalization of CENP-A suggests a distinct nucleosome structure at the inner kinetochore plate of active centromeres. Curr. Biol. CB 7: 901–904

Wignall SM, Deehan R, Maresca TJ & Heald R (2003) The condensin complex is required for proper spindle assembly and chromosome segregation in Xenopus egg extracts. J. Cell Biol. 161: 1041–1051

Willard HF & Waye JS (1987) Hierarchical order in chromosome-specific human alpha satellite DNA. Trends Genet. 3: 192–198

Worcel A, Han S & Wong ML (1978) Assembly of newly replicated chromatin. Cell 15: 969–977

Yu Z, Zhou X, Wang W, Deng W, Fang J, Hu H, Wang Z, Li S, et al (2015) Dynamic Phosphorylation of CENP-A at Ser68 Orchestrates Its Cell-Cycle-Dependent Deposition at Centromeres. Dev. Cell 32: 68–81

Zeitlin SG, Baker NM, Chapados BR, Soutoglou E, Wang JYJ, Berns MW & Cleveland DW (2009) Double-strand DNA breaks recruit the centromeric histone CENP-A. Proc. Natl. Acad. Sci. U. S. A. 106: 15762–15767

Conclusions

245

Zeitlin SG, Chapados BR, Baker NM, Tai C, Slupphaug G & Wang JYJ (2011) Uracil DNA N-Glycosylase Promotes Assembly of Human Centromere Protein A. PLoS ONE 6: e17151

Zeitlin SG, Patel S, Kavli B & Slupphaug G (2005) Xenopus CENP-A assembly into chromatin requires base excision repair proteins. DNA Repair 4: 760–772

Documents

Mischa Andriessen - run.unl.pt